www.hematologicaloncology.com
Vol. 39 Supp. 2 June 2021
ISSN 0278–0232
Abstracts from the 16th International Conference on Malignant Lymphoma,
Lugano, Switzerland
Virtual edition, June 18–22, 2021
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Hematological Oncology
18
Hematological
ONCOLOGY
Editor-in-Chief
Francesco Bertoni
J. Westermann
Berlin, Germany
H. Zhang
Tianjin, China
E. Zucca
Bellinzona, Switzerland
M. Ponzoni
Milan, Italy
D. Rossi
Bellinzona, Switzerland
K. Tobinai
Tokyo, Japan
R.W. Tsang
Toronto, Canada
Govind Bhagat
Hui Wei
Editorial Board
M. Dreyling
Groβhadern, Germany
M. Gramatzki
Kiel, Germany
P. Johnson
Southampton, UK
S. Nakamura
Nagoya, Japan
Andrés J.M. Ferreri
Associate Editors
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Aims and Scope
Hematological Oncology
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PEARLS OF
Knowledge
EXPERT PERSPECTIVES IN THE TREATMENT OF R/R DLBCL
Time is precious: Take 50 minutes
out of your ICML agenda to view
our innovative series of short video
presentations, where 10 clinical experts
discuss current treatment options and
research into potential new therapies
for their patients with R/R DLBCL.
Driving the understanding of DLBCL forward
The live 50-minute session
will take place at
16:00 (CEST) on 18 June 2021.
Following the congress, all
10 videos will be available to view
on demand on the ICML website.
CH/TAFACD19/NP/21/0004
Date of preparation: April 2021
A virtual educational event organised and sponsored by Incyte Biosciences International Sàrl
© 2021, Incyte Biosciences International Sàrl. All rights reserved
Hematological Oncology
Vol. 39 Suppl. 2 June 2021
16th Internaonal Conference on Malignant Lymphoma
Contents
Patients give their all. So do we.
Within each and every patient lies the potential
to create a living cell therapy. We are deeply
committed to advancing cell therapy—by
pursuing scientific breakthroughs, pioneering
a pipeline of innovative constructs, and utilizing
novel manufacturing.
Advancing Cell Therapy
BMS invests in Europe with new cell therapy
manufacturing site planned in the Netherlands.
As part of Bristol Myers Squibb’s continuing
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Stay tuned as the new site progresses.
www.bms.com
WITH EVERY
IN THEIR BEING
© 2021 Bristol Myers Squibb Company.
4/21. HE-CH-2100066
DOI: 10.1002/hon.2877
SUPPLEMENT ARTICLE
ACKNOWLEDGEMENTS
INTERNATIONAL CONFERENCE ON MALIGNANT LYMPHOMA (ICML) and
FOUNDATION FOR THE INSTITUTE OF ONCOLOGY RESEARCH (IOR) PRESIDENT
Franco Cavalli, Bellinzona (Switzerland)
ICML ORGANIZING COMMITTEE CHAIRMAN
Francesco Bertoni, Bellinzona (Switzerland)
ICML ORGANIZING COMMITTEE (based in Bellinzona)
Michele Ghielmini
Alden Moccia
Bertrand Nadel, Marseilles (France) ‐Representative of American Association for Cancer Research (AACR)
Fedro Peccatori, Milan (Italy) ‐Representative of European School of Oncology (ESO)
Davide Robbiani
Davide Rossi
Anastasios Stathis
Georg Stüssi
Emanuele Zucca
16‐ICML ADVISORY BOARD
James O. Armitage, Omaha, NE (USA) ‐CHAIRMAN
Elias Campo, Barcelona (Spain)
Bruce D. Cheson, Washington, D.C. (USA),
Nicholas Chiorazzi, Manhasset, NY (USA),
Wee Joo Chng, Singapore (Singapore)
Riccardo Dalla‐Favera, New York, NY (USA)
Stephan Dirnhofer, Basel (Switzerland)
Martin Dreyling, Munich (Germany)
Jonathan W. Friedberg, Rochester, NY (USA)
Gianluca Gaidano, Novara (Italy)
Philippe Gaulard, Créteil (France)
Mary K. Gospodarowicz, Toronto, ON (Canada),
Peter W.M. Johnson, Southampton (UK),
Brad S. Kahl, St. Louis, MO (USA)
Ralf K üppers, Essen (Germany),
John P. Leonard, New York, NY (USA),
T. Andrew Lister, London (UK)
Markus G. Manz, Zurich (Switzerland)
Ari M. Melnick, New York, NY (USA)
Koichi Ohshima, Kurume (Japan)
Astrid Pavlovsky, Buenos Aires (Argentina)
Leticia Quintanilla‐Martinez de Fend, Tübingen (Germany)
© 2021 The Authors. Hematological Oncology published by John Wiley & Sons Ltd.
Hematological Oncology. 2021;39(S2):7–12. wileyonlinelibrary.com/journal/hon
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S.Vincent Rajkumar, Rochester, MN (USA)
Kerry J. Savage, Vancouver BC (Canada)
John F. Seymour, Melbourne (Australia)
Margaret A. Shipp, Boston, MA (USA)
Lena Specht, Copenhagen (Denmark)
Catherine Thieblemont, Paris (France)
Pier Luigi Zinzani, Bologna (Italy)
Wilhelm Wössmann, Hamburg (Germany)
Weili Zhao, Shangai (China)
CONFERENCE SECRETARIAT
Cristiana Brentan, Federica Cariglia, Angela Kurtz, Orietta Lugli, Chiara Saporiti
Foundation for the Institute of Oncology Research (IOR) Via Vela 6, CH‐6500 Bellinzona
The Organizers would like to express their sincere gratitude to the Industry Partners who continue to support the Conference. Their
unrestricted support is essential to the dissemination of the Scientific and Industry programs to the worldwide community engaged in the study
and treatment of lymphoid neoplasms:
AbbVie, Inc.
Acrotech Biopharma LLC
ADC Therapeutics
AstraZeneca
Bayer
BeiGene
Bristol Myers Squibb
Clinigen
CRISPR Therapeutics
Daiichi Sankyo
F. Hoffmann‐La Roche
Genmab
Gilead Sciences Europe Ltd.
HTG Molecular Diagnostics
Incyte
Janssen Oncology Pharmaceutical Companies of Johnson & Johnson
Karyopharm
Loxo Oncology at Lilly
Lymphoma Hub
Miltenyi Biomedicine
MorphoSys
MSD
Novartis Oncology
Pfizer Oncology
Regeneron
Takeda
VJHemOnc
(updated on May 2021)
The Organizers would like to express their sincere gratitude to the following Partners for their precious support, essential to the organization of
this Virtual edition of the Conference and to the achievement of its objectives:
American Association for Cancer Research – AACR
City of Lugano
European School of Oncology – ESO
European School of Oncology Foundation – ESOF
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European Society for Medical Oncology – ESMO
IBSA Foundation for Scientific Research
International Extranodal Lymphoma Study Group ‐IELSG
International Lymphoma Radiation Oncology Group ‐ILROG
Lymphoma Coalition
Saudi Society of Blood & Marrow Transplantation ‐SS‐BMT
Swiss Cancer Research Foundation
Union for China Lymphoma Investigators ‐UCLI
Università della Svizzera Italiana ‐USI
(updated on May 2021)
16‐ICML REVIEWERS’ LIST
The 16‐ICML Organizing Committee wishes to thank the following colleagues and friends for their professional help:
S.M. Ansell, Rochester, MN (USA)
J.O. Armitage, Omaha, NE (USA)
S.F. Barrington, London (UK)
T.T. Batchelor, Boston, MA (USA)
E. Campo, Barcelona (Spain)
C. Casulo, Rochester, NY (USA)
L. Cerchietti, New York, NY (USA)
L. Ceriani, Bellinzona (Switzerland)
B.D. Cheson, Washington, D.C. (USA)
N. Chiorazzi, Manhasset, NY (USA)
A. Conconi, Biella (Italy)
A. Condoluci, Bellinzona (Switzerland)
A. Davies, Southampton (UK)
L. de Leval, Lausanne (Switzerland)
S. Dirnhofer, Basel (Switzerland)
M. Dreyling, Munich (Germany)
A.J. Ferreri, Milan (Italy)
J.W. Friedberg, Rochester, NY (USA)
P. Gaulard, Créteil (France)
M.K. Gospodarowicz, Toronto, ON (Canada)
P.W.M. Johnson, Southampton (UK)
B.S. Kahl, St. Louis, MO (USA)
R. Küppers, Essen (Germany)
S. Le Gouill, Nantes (France)
J.P. Leonard, New York, NY (USA)
T.A. Lister, London (UK)
S. Luminari, Modena (Italy)
M. Manz, Zurich (Switzerland)
M. Martelli, Rome (Italy)
M. Meignan, Creteil (France)
A.M. Melnick, New York, NY (USA)
F. Morschhauser, Lille (France)
B. Nadel, Marseille (France)
U. Novak, Bern (Switzerland)
G.S. Nowakowski, Rochester, MN (USA)
L. Pasqualucci, New York, NY (USA)
A. Pavlovsky, Buenos Aires (Argentina)
L. Quintanilla‐Martinez de Fend, Tübingen (Germany)
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C. Renner, Homburg (Germany)
G. Salles, New York, NY (USA)
K.J. Savage, Vancouver, BC (Canada)
S. Schuster, Philadelphia, PA (USA)
J.F. Seymour, Melbourne (Australia)
M.A. Shipp, Boston, MA (USA)
L. Specht, Copenhagen (Denmark)
C. Thieblemont, Paris (France)
K. Tobinai, Tokyo (Japan)
W. Wössmann, Hamburg (Germany)
W. Zhao, Shanghai (China)
T. Zenz, Zurich (Switzerland)
P.L. Zinzani, Bologna (Italy)
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DOI: 10.1002/hon.2878
SUPPLEMENT ARTICLE
SCIENTIFIC PROGRAM (updated on June 2, 2021)
All session times for the 16‐ICML are Central European Summer Time (CEST)
Saturday, June 19
Time Session Article/ abstract nr.
13:00 – 13:45 “Meet the Professor” session
What's new in peripheral T‐cell lymphomas EB 06
Stefano Luminari, Reggio Emilia (Italy)
Live Q&A
13:00 – 13:45 “Meet the Professor” session
Cutaneous T‐cell lymphomas – an update 2021 EB 05
Werner Kempf, Zürich (CH)
Live Q&A
13:00 – 13:45 “Meet the Professor” session
Personalised medicine for Hodgkin Lymphoma: mitigating toxicity while preserving cure EB 04
Peter W.M. Johnson, Southampton (UK)
Live Q&A
13:00 – 13:45 “Meet the Professor” session
Use of available prognostic scores in treatment decision: beyond standard prognostic
scores to include molecular/genetics/imaging
John F. Seymour, Melbourne (Australia)
Live Q&A
14:00 – 15:00 Opening of the conference
Welcome to attendees
Franco Cavalli, Bellinzona (Switzerland)
Henry Kaplan Memorial Lecture and ICML Prize
Laudatio: Franco Cavalli, Bellinzona (Switzerland)
Towards control of chronic lymphocytic leukemia with targeted agents 001
Michael Hallek, Cologne (Germany)
15:15 – 16:45 Plenary session
Co‐chairs: James Armitage, Omaha, NE (USA) and Franco Cavalli, Bellinzona (Switzerland)
Pervasive Hypermutation of Super‐enhancer Regions Dysregulates Oncogene Expression
in Diffuse Large B‐cell Lymphoma
004
Elodie Bal, New York, NY (USA)
Introduced by Ralf Küppers, Essen (Germany)
(Continues)
© 2021 The Authors. Hematological Oncology published by John Wiley & Sons Ltd.
Hematological Oncology. 2021;39(S2):13–25. wileyonlinelibrary.com/journal/hon
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(Continued)
Saturday, June 19
Time Session Article/ abstract nr.
Live Q&A moderated by session chairs
Early Positron Emission Tomography Response‐Adapted Treatment in Localized Diffuse
Large B‐Cell Lymphoma (aaIPI=0): Results of the Phase 3 LYSA LNH 09‐1B Trial.
005
Serge Bologna, Essey lès Nancy (France)
Introduced by Jonathan W. Friedberg, Rochester, NY (USA)
Live Q&A moderated by session chairs
Determinants of resistance to engineered T‐cell therapies targeting CD19 in lymphoma 006
Brian Sworder, Stanford, CA (USA)
Introduced by Stephen J. Schuster, Philadelphia, PA (USA)
Live Q&A moderated by session chairs
17:00 – 18:15 AACR‐ICML joint session
Artificial intelligence in lymphoma diagnosis and treatment
Co‐chairs: Riccardo Dalla‐Favera, New York, NY (USA), Bertrand Nadel, Marseille (France)
and Olivier Elemento, New York, NY (USA)
Artificial intelligence and medicine: past and future 007
Luca M. Gambardella, Lugano (Switzerland)
Artificial intelligence and pathology 008
Pierre Brousset, Toulouse (France)
Use of deep learning to analyse and exploit molecular data 009
Dan A. Landau, New York, NY (USA)
How Machine Learning can enhance clinical development 010
Paul Trichelair, Paris (France)
Live Q&A moderated by session chairs
Saturday, June 20
Time Session Article/ abstract nr.
12:00 – 13:30 UCLI‐ICML joint session
New data on T‐cell and other lymphomas
Honorary co‐chairs: Franco Cavalli, Bellinzona (Switzerland) and Jun Ma, Harbin (China)
Executive co‐chairs: Stefano Luminari, Reggio Emilia (Italy) and Jun Zhu, Beijing (China)
Welcome
Jun Zhu, Beijing (China)
T‐cell lymphoma biopathology: what is new?
Laurence de Leval, Lausanne (Switzerland)
The epidemiology of malignant lymphoid diseases in China
Yu‐qin Song, Beijing (China)
Recent advances in Extranodal Natural Killer/T‐Cell Lymphoma: experiences from the SYSUCC
Qing‐qing Cai, Guangzhou (China)
New treatment options in T‐cell lymphoma
Stefano Luminari, Reggio Emilia (Italy)
The changing faces of EBV+T/NK‐cell lymphomas: diagnostic challenges and advances
Xiao‐qiu Li, Shanghai (China)
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(Continued)
Saturday, June 20
Time Session Article/ abstract nr.
Closure Stefano Luminari, Reggio Emilia (Italy)
12:30 – 13:30 “Innovation in radiotherapy – new dose/fractionation schedules”
Workshop organised by the International Lymphoma Radiation Oncology Group (ILROG)
Chair: Lena Specht, Copenhagen (Denmark)
Radiation doses in the treatment of lymphomas – what is the evidence?
Peter Hoskin, Manchester (UK)
Low‐dose regimens – new fractionation schemes for indolent lymphomas
Joachim Yahalom, New York, NY (USA)
Fewer but larger fractions in lymphoma radiotherapy – experience from the COVID
emergency fractionation
Lena Specht, Copenhagen (Denmark)
14:00 – 14:45 Gianni Bonadonna Memorial Lecture
(in collaboration with American Association for Cancer Research AACR)
Laudatio: Davide Rossi, Bellinzona (Switzerland)
The architecture of liquid biopsy research for lymphoma monitoring 002
Ash A. Alizadeh, Stanford, CA (USA)
15:00 – 16:30 Educational symposium on High risk follicular lymphoma
Chair: Brad Kahl, Saint Louis, MO (USA)
Upfront identification of high risk follicular lymphoma EB 12
Carla Casulo, Rochester, NY (USA)
Vulnerabilities in the tumor and microenvironment in follicular lymphoma EB 11
Elias Campo, Barcelona (Spain)
High risk follicular lymphoma: treatment options EB 13
Brad Kahl, Saint Louis, MO (USA)
Live Q&A moderated by session chair
16:45 – 17:15 “Meet the Professor” session
Molecular diagnostics and reporting in lymphoid malignancies: current status and beyond EB 09
Richard Rosenquist Brandell, Stockholm (Sweden)
Live Q&A
16:45 – 17:15 “Meet the Professor” session
New drugs and pharmacological interactions in real life EB 10
Anastasios Stathis, Bellinzona (Switzerland)
Live Q&A
16:45 – 17:30 “Meet the Professor” session
Mantle cell lymphoma ‐advances in molecular biology, prognostication and treatment
approaches
EB 03
Martin Dreyling, Munich (Germany)
Live Q&A
16:45 – 17:30 “Meet the Professor” session
(Continues)
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(Continued)
Saturday, June 20
Time Session Article/ abstract nr.
Recognizing but not harming. Borderline B‐cell lymphoid proliferations EB 07
Leticia Quintanilla‐Martinez de Fend, Tübingen (Germany)
Live Q&A
17:45 – 19:15 Session 1: NEW THERAPEUTICS
Co‐chairs: Francesco Bertoni, Bellinzona (Switzerland) and Gilles Salles, New York, NY (USA)
Targeting proximal BCR signaling pathway in diffuse large B‐cell lymphoma 011
Jae Woo Choi, Bethesda, MD (USA)
MALT1 degradation for the treatment of Activated B‐Cell type Diffuse Large B‐cell Lymphoma 012
Madhav Seshadri, New York, NY (USA)
KT‐413, a novel IRAKIMiD Degrader of IRAK4 and IMiD substrates, has a differentiated MOA
that leads to single‐agent and combination regressions in MYD88MT Lymphoma models
013
Duncan Walker, Watertown, MA (USA)
Live Q&A moderated by session chairs
First‐in‐human study of the EZH1 and EZH2 dual inhibitor valemetostat tosylate (DS‐3201b)
in patients with relapsed or refractory non‐Hodgkin lymphomas
014
Kenj Ishitsuka, Kagoshima (Japan)
Glofitamab step‐up dosing: updated efficacy data show high complete response rates in heavily
pretreated relapsed/refractory (R/R) non‐Hodgkin lymphoma (NHL) patients
015
Carmelo Carlo‐Stella, Milan (Italy)
Subcutaneous Epcoritamab in Patients With Relapsed/Refractory B‐Cell Non‐Hodgkin
Lymphoma: Safety Profile and Anti‐tumor Activity
016
Martin Hutchings, Copenhagen (Denmark)
Live Q&A moderated by session chairs
17:45 – 19:15 Session 2: LYMPHOMA IMAGING
Co‐chairs: Sally F. Barrington, London (UK) and Josée Zijlstra‐Baalbergen, Amsterdam
(Netherlands)
Defining ultra‐high‐risk DLBCL patients prior to initial treatment based on an integrative host
and disease prognostic score (from REMARC study)
017
Catherine Thieblemont, Paris (France)
Integration of baseline metabolic parameters and mutational profile predicts outcome in
DLBCL patients. A post hoc analysis of SAKK38/07 study.
018
Guido Ghilardi, Bellinzona (Switzerland)
Baseline Metabolic Tumor Volume and IPS predict ABVD failure in advanced‐stage Hodgkin
Lymphoma with a negative interim PET scan after two chemotherapy cycles. A
retrospective analysis from the GITIL/FIL HD0607 trial
019
Andrea Gallamini, Nice (France)
Live Q&A moderated by session chairs
Prognostic role of lesion dissemination feature (Dmax) calculated on baseline PET/CT in
Hodgkin Lymphoma
020
Rexhep Durmo, Modena (Italy)
Predictive value of quantitative 18F‐FDG‐PET‐CT radiomics analysis in 174 patients with
relapsed/refractory classical Hodgkin lymphoma
021
Julia Driessen, Amsterdam (Netherlands)
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(Continued)
Saturday, June 20
Time Session Article/ abstract nr.
Development and validation of a PET radiomics prognostic model for diffuse large B cell
lymphoma
022
Luca Ceriani, Bellinzona (Switzerland)
Live Q&A moderated by session chairs
17:45 – 19:15 Session 3: AGGRESSIVE LYMPHOMAS
Co‐chairs: Peter M.W. Johnson, Southampton (UK) and Margaret Shipp, Boston, MA (USA)
Clonal Hematopoiesis is associated with inferior prognosis in newly diagnosed Diffuse Large B‐
Cell Lymphoma patients
023
Jan L. Boegeholz, Stanford, CA (USA)
Whole genome sequencing of matched primary and relapsed DLBCL reveals distinct
evolutionary dynamics associated with relapse timing
024
Laura K. Hilton, Vancouver, B.C. (Canada)
Phased variants improve DLBCL minimal residual disease detection at the end of therapy 025
David Kurtz, Stanford, CA (USA)
Live Q&A moderated by session chairs
Genetic Subtype Guided Rituximab‐based Immunochemotherapy Improves Outcome in Newly
Diagnosed Diffuse Large B‐cell Lymphoma: First Report of a Randomized Phase 2 Study
026
Muchen Zhang, Shanghai (China)
Biomarker‐driven treatment strategy in high risk diffuse large B‐cell lymphoma: Results of a
Nordic phase 2 study
027
Sirpa Leppä, Helsinki (Finland)
Long‐term analyses from L‐MIND, a Phase II study of tafasitamab plus lenalidomide (LEN) in
patients (pts) with relapsed or refractory diffuse large B‐cell lymphoma (R/R DLBCL)
028
Johannes Duell, Würzburg (Germany)
Live Q&A moderated by session chairs
17:45 – 19:15 Session 4: CHRONIC LYMPHOCYTIC LEUKEMIA
Co‐chairs: Susan O’Brien, Orange, CA (USA) and Kostas Stamatopoulos, Thessaloniki (Greece)
Adaptation of chronic lymphocytic leukemia to ibrutinib is mediated by epigenetic plasticity of
residual disease and by‐pass signaling via MAPK pathway
029
Lodovico Terzi di Bergamo, Bellinzona (Switzerland)
Genetic markers and outcome with front line obinutuzumab plus either chlorambucil or
venetoclax ‐updated analysis of the CLL14 trial
030
Eugen Tausch, Ulm (Germany)
Venetoclax‐obinutuzumab modulates clonal growth: Results of a population‐based minimal
residual disease model from the randomized CLL14 study
031
Othman Al‐Sawaf, Cologne (Germany)
Live Q&A moderated by session chairs
CAPTIVATE primary analysis of first‐line treatment with fixed‐duration ibrutinib plus
venetoclax for chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL)
032
Constantine Tam, Melbourne (Australia)
First Results of a Head‐to‐Head Trial of Acalabrutinib versus Ibrutinib in Previously Treated
Chronic Lymphocytic Leukemia
033
Peter Hillmen, Leeds (UK)
(Continues)
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(Continued)
Saturday, June 20
Time Session Article/ abstract nr.
Bendamustine, followed by Obinutuzumab, Acalabrutinib and Venetoclax in patients (pts) with
relapsed/refractory chronic lymphocytic leukemia (CLL): CLL2‐BAAG trial of the GCLLSG
034
Paula Cramer, Cologne (Germany)
Live Q&A moderated by session chairs
Monday, June 21
Time Session Article/ abstract nr.
12:30 – 13:30 “The evolving role of Radiotherapy in the salvage treatment for lymphoma in the era of
CAR‐T therapy”
Workshop organised by the International Lymphoma Radiation Oncology Group (ILROG)
Chair: Bouthaina S. Dabaja, Houston, TX (USA)
Radiation prior to immune‐cellular therapy: the science behind the sublethal immunogenic
cell death
Richard Tsang, Toronto, ON (Canada)
Optimal integration of radiation in salvage therapy for relapsed / refractory lymphoma
(including CAR‐T)
Richard Tsang, Toronto, ON (Canada)
Ongoing clinical trials combining radiation and CAR‐T
George Mikhaeel, London (UK)
14:00 – 14:45 John Ultmann Memorial Lecture
(in collaboration with European School of Oncology, ESO)
Laudatio: Emanuele Zucca, Bellinzona (Switzerland)
Immune Suppression and Dysfunction in the Tumor Microenvironment in Lymphoma 003
Stephen M. Ansell, Rochester, MN (USA)
15:00 – 16:30 Educational symposium on Immunotherapy
Chair: Gilles Salles, New York, NY (USA)
Optimizing CAR T cell therapy in lymphoma EB 15
Gilles Salles, New York, NY (USA)
Allogeneic stem cell transplant in non‐Hodgkin lymphomas: still an indication? EB 14
Peter Dreger, Heidelberg (Germany)
Bispecific Antibodies for the Treatment of Lymphomas: Promises and Challenges EB 15
Stephen J. Schuster, Philadelphia, PA (USA)
Live Q&A moderated by session chair
16:45 – 17:45 “The challenging case” session
Aggressive NHL
Chair: Franco Cavalli, Bellinzona (Switzerland)
Case 1: “A patient with abdominal pain”
Discussant: Ranjana H. Advani, Stanford, CA (USA)
Case 2: “Can we offer a curative treatment to patients with relapsed DLBCL who are not a
candidate for autologous stem cell transplant?”
Discussant: Urban Novak, Bern (Switzerland)
Case 3: “How should I treat patients with MCL relapsing in CNS?”
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Monday, June 21
Time Session Article/ abstract nr.
Discussant: Martin Dreyling, Munich (Germany)
Case 4: “A 31 year old man with dysphagia”
Discussant: Pier Luigi Zinzani, Bologna (Italy)
16:45 – 17:45 “The challenging case” session
Indolent NHL and CLL
Chair: Davide Rossi, Bellinzona (Switzerland)
Case 1: “A young patient with leg swelling”
Discussant: Ranjana H. Advani, Stanford, CA (USA)
Case 2: “The gentleman with acid peptic disease”
Discussant: Mary Gospodarowicz, Toronto, ON (Canada)
Case 3: “A woman with high‐risk CLL and tachycardia”
Discussant: Barbara Eichhorst, Cologne (Germany)
Case 4: “A young man with triple refractory CLL”
Discussant: Barbara Eichhorst, Cologne (Germany)
16:45 – 17:45 “The challenging case” session
Hodgkin Lymphoma
Chair: Alden Moccia, Bellinzona (Switzerland)
Case 1: “A sportsman with shortness of breath”
Discussant: John Kuruvilla, Toronto, ON (Canada)
Case 2: “A late relapse Hodgkin lymphoma”
Discussant: Peter W.M. Johnson, Southampton (UK)
Case 3: “A 73 year‐old woman in the ER”
Discussant: James O. Armitage, Omaha, NE (USA)
Case 4: “A sportsman with enlarged lymph nodes”
Discussants: Peter Borchmann, Cologne (Germany) and Steven Le Gouill, Nantes (France)
16:45 – 17:45 “The challenging case” session
Difficult pathological cases
Chair: Luca Mazzucchelli, Locarno (Switzerland)
Discussants: Stefan Dirnhofer, Basel (Switzerland) and Alexandar Tzankov, Basel
(Switzerland)
18:00 – 18:45 “Meet the Professor” session
Sequencing of myeloma therapy: finding the right path among many standards EB 08
S. Vincent Rajkumar, Rochester, MN (USA)
Live Q&A
18:00 – 18:45 “Meet the Professor” session
Langerhans Cell Histiocytosis: Version 2021 EB 01
Carl E. Allen, Houston, TX (USA)
Live Q&A
18:00 – 18:45 “Meet the Professor” session
(Continues)
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(Continued)
Monday, June 21
Time Session Article/ abstract nr.
Molecular classification of aggressive lymphomas – past, present, future EB 02
Björn Chapuy, Göttingen (Germany)
Live Q&A
18:00 – 18:45 IBSA Foundation Special Forum
Welcome
Silvia Misiti, Lugano (Switzerland)
Introduction
Andrea Alimonti, Bellinzona (Switzerland)
Vaccines and monoclonals to regain our freedom
Rino Rappuoli, Siena (Italy)
19:00 – 20:00 THE BIG DEBATE: “DLBCL: one disease, one treatment?”
organized by the Oncology Institute of Southern Switzerland (IOSI)
(supported by an unrestricted educational grant from GILEAD SCIENCES)
Chair: Emanuele Zucca, Bellinzona (Switzerland)
DEBATE 1: Are we ready to introduce genetic classification in routine diagnostics?
YES. Treatment improvement will not be possible otherwise.
Björn Chapuy, Göttingen (Germany)
NO. This is not yet feasible in everyday community settings.
Leticia Quintanilla Martinez – de Fend, Tübingen (Germany)
DEBATE 2: Is frontline R‐CHOP still the sole standard?
YES. R‐CHOP21 remains the standard of care.
Laurie Sehn, Vancouver B.C. (Canada)
NO. We have already moved beyond R‐CHOP.
Grzegorz S. Nowakowski, Rochester, MN (USA)
DEBATE 3: Will targeted treatments soon inform frontline management?
YES. Precision medicine will allow patient‐tailored treatment.
Margaret Shipp, Boston, MA (USA)
NO. CART and agnostic immunotherapies will replace chemotherapy.
Stephen J. Schuster, Philadelphia, PA (USA)
19:00 – 20:30 Session 5 : PEDIATRIC LYMPHOMAS
Chair: Wilhelm Wössmann, Hamburg (Germany)
Current Status and Challenges in Diagnosis of Childhood NHL 035
Wolfram Klapper, Kiel (Germany)
Dose‐adjusted EPOCH‐rituximab or intensified B‐NHL‐BFM‐type Therapy for Pediatric
Primary Mediastinal B‐cell Lymphoma
036
Fabian Knörr, Hamburg (Germany)
An Open‐label, Phase 1/2 Study of Frontline Brentuximab Vedotin +Adriamycin,
Vinblastine, and Dacarbazine in Paediatric Patients with Advanced Stage Hodgkin
Lymphoma
037
Anna Franklin, Aurora, CO (USA)
20
-
(Continued)
Monday, June 21
Time Session Article/ abstract nr.
Brentuximab Vedotin with Chemotherapy in Adolescents and Young Adults (AYAs) with
Stage III or IV Hodgkin Lymphoma: a Subgroup Analysis From the Phase 3 ECHELON‐1
Study
038
Howland Crosswell, Greenville, SC (USA)
A UK population‐based study of non‐Hodgkin Lymphoma in Teenagers and Young Adults
(TYA) ‐Incidence, treatment and outcomes
039
Robert Carr, London (UK)
Live Q&A moderated by session chair
Tuesday, June 22
Time Session Article/ abstract nr.
13:00 – 14:30 Session 6: LYMPHOMA BIOLOGY 1
Co‐chairs: Elias Campo, Barcelona (Spain) and Ari M. Melnick, New York, NY (USA)
Molecular Subclusters of Follicular Lymphoma: a report from the UK’s Haematological
Malignancy Research Network
040
Reuben Tooze, Leeds (UK)
Somatic Alterations in Follicular Lymphoma Associate with unique Tumor‐Cell
Transcriptional States and Tumor‐Immune Microenvironments.
041
Jordan Krull, Rochester, MN (USA)
CREBBP mediated acetylation of KMT2D in normal and transformed GC B cells 042
Sofija Vlasevska, New York, NY (USA)
Live Q&A moderated by session chairs
Genetic and Phenotypic Attributes of Splenic Marginal Zone Lymphoma 043
Francesca Guidetti, Bellinzona (Switzerland)
Monomorphic Epitheliotropic Intestinal T‐cell Lymphoma (MEITL) : clinico‐pathological
analysis of a multicenter European cohort.
044
Doriane Cavalieri, Clermont‐Ferrand, France
RHOA G17V potentiates CD28 T195P mutation induced NFAT transcriptional activity
upon CD3/CD28 stimulation
045
David Vallois, Lausanne (Switzerland)
Live Q&A moderated by session chairs
13:00 – 14:30 Session 7: AGGRESSIVE EXTRANODAL ENTITIES
Co‐chairs: Mary K. Gospodarowicz, Toronto, ON (Canada) and Grzegorz S. Nowakowski,
Rochester, MN (USA)
Noninvasive detection, classification, and risk stratification of primary CNS lymphomas by
ctDNA profiling
046
Jurik A. Mutter, Freiburg (Germany)
MATRix induction followed by autologous stem cell transplant or whole‐brain irradiation in
primary CNS lymphoma. 7‐year results of the IELSG32 randomized trial.
047
Andrés J.M. Ferreri, Milan (Italy)
Intensified (intravenous and intrathecal) CNS prophylaxis in primary testicular diffuse large
B‐cell lymphoma: 5‐year results of the IELSG30 trial.
048
Annarita Conconi, Biella (Italy)
Live Q&A moderated by session chairs
(Continues)
-
21
(Continued)
Tuesday, June 22
Time Session Article/ abstract nr.
Impact of different induction regimens on the outcome of primary mediastinal B cell
lymphoma in the prospective IELSG 37 trial
049
Emanuele Zucca, Bellinzona (Switzerland)
Outcomes after first‐line immunochemotherapy for primary mediastinal B cell lymphoma
patients: a LYSA study
050
Vincent Camus, Rouen (France)
Nivolumab plus brentuximab vedotin for relapsed/refractory primary mediastinal large B‐
cell lymphoma: Extended follow‐up from the phase 2 CheckMate 436 study
051
Pier Luigi Zinzani, Bologna (Italy)
Live Q&A moderated by session chairs
13:00 – 14:30 Session 8: PERIPHERAL T/NK‐CELL LYMPHOMAS
Co‐chairs: Stefano Luminari, Reggio Emilia (Italy) and Julie M. Vose, Omaha, NE (USA)
ESA versus MESA with sandwiched radiotherapy in patients with early‐stage natural killer/
T‐cell lymphoma: a multicentre, randomised, phase 3, non‐inferiority trial
052
Hui‐Juan Zhong, Shanghai (China)
Allogeneic hematopoietic cell transplantation for peripheral T‐cell lymphoma: Comparable
outcomes of haplo‐identical vs. matched donors. A CIBMTR & EBMT Analysis
053
Peter Dreger, Heidelberg (Germany)
Lacutamab in patients (pts) with advanced mycosis fungoides (MF) according to KIR3DL2
expression: early results from the TELLOMAK phase 2 trial
054
Martine Bagot, Paris (France)
Live Q&A moderated by session chairs
Multi‐center phase II study of romidepsin plus lenalidomide for patients with previously
untreated peripheral T‐cell lymphoma (PTCL)
055
Jia Ruan, New York, NY (USA)
The Combination of Duvelisib and Romidepsin (DR) Is Highly Active Against Relapsed/
Refractory Peripheral T‐cell Lymphoma with Low Rates of Transaminitis: Final Results
056
Steven M. Horwitz, New York, NY (USA)
Early Safety and Efficacy Data from a Phase I/II Trial of DZD4205, a Selective JAK1
Inhibitor, in Relapsed/Refractory Peripheral T‐Cell Lymphoma
057
Won‐Seog Kim, Seoul (South Korea)
Live Q&A moderated by session chairs
13:00 – 14:30 Session 9: MANTLE CELL LYMPHOMA
Co‐chairs: Martin Dreyling, Munich (Germany) and John P. Leonard, New York, NY (USA)
A simple epigenetic signature defines two biologic groups of mantle cell lymphoma 058
Marco M. Bühler, Barcelona (Spain)
A completely genetic prognostic model overcomes clinical prognosticators in mantle cell
lymphoma: results from the MCL0208 trial from the Fondazione Italiana Linfomi (FIL)
059
Simone Ferrero, Turin (Italy)
Efficacy and safety of ibrutinib in combination with rituximab as frontline treatment for
indolent clinical forms of mantle cell lymphoma. Results of the GELTAMO IMCL‐2015
study
060
Eva Giné, Barcelona (Spain)
Live Q&A moderated by session chairs
22
-
(Continued)
Tuesday, June 22
Time Session Article/ abstract nr.
The combination of venetoclax, lenalidomide and rituximab in patients with newly
diagnosed mantle cell lymphoma induces high response rates and MRD undetectability.
061
Tycel J. Phillips, Ann Arbor, MI (USA)
SAKK 36/13 ‐Ibrutinib plus bortezomib and ibrutinib maintenance for relapsed and
refractory mantle cell lymphoma: final report of a Phase I/II trial of the European MCL
network
062
Urban Novak, Bern (Switzerland)
MCL Induction R
2
followed by maintenance in patients with relapsed/refractory mantle cell
lymphoma: Interim analysis from the Phase 3b MAGNIFY study
063
Jeff P. Sharman, Eugene, OR (USA)
14:45 – 16:15 Session 10: LYMPHOMA BIOLOGY 2
Co‐chairs: Ralf Küppers, Essen (Germany) and Laura Pasqualucci, New York, NY (USA)
The topology of MYC rearrangements in double‐hit lymphoma is constrained by the
preceding IGH‐BCL2 rearrangement – an LLMPP project
064
Laura K. Hilton, Vancouver, B.C. (Canada)
The mutational landscape of double/triple‐hit high‐grade B‐cell lymphoma with BCL2
rearrangement (DH/TH‐BCL2) – an LLMPP project
065
Brett J. Collinge, Vancouver, B.C. (Canada)
Do Cell‐of‐Origin, Double Expresser, and Double Hit Status Affect Outcomes in Relapsed/
Refractory Diffuse Large B Cell Lymphoma (R/R DLBCL)? A Prospective Observational
Study.
066
Sanjal H. Desai, Rochester, MN (USA)
Live Q&A moderated by session chairs
Copy number variation analysis identifies distinct genomic features in adult Burkitt
lymphoma
067
Kostiantyn Dreval, Burnaby, B.C. (Canada)
Key genetic and molecular aberrations identified in both adult and EBV‐positive Burkitt
lymphoma patients
068
Nicole Thomas, Burnaby, B.C. (Canada)
Triple positive (CD10+BCL6+MUM1+) diffuse large B‐cell lymphomas in adults are a
heterogeneous group enriched in large B‐cell lymphomas with IRF4 rearrangement
069
Leonie Frauenfeld, Tübingen (Germany)
Live Q&A moderated by session chairs
14:45 – 16:15 Session 11: HODGKIN LYMPHOMA
Co‐chairs: Ranjana H. Advani, Stanford, CA (USA) and Bruce D. Cheson, Washington, D.C.
(USA)
Circulating tumor DNA is a prognostic biomarker in classic Hodgkin lymphoma 070
Maria Cristina Pirosa, Bellinzona (Switzerland)
Relapses in interim PET‐negative limited‐stage Hodgkin lymphoma patients receiving
ABVD with or without radiotherapy – Analysis of EORTC/FIL/LYSA H10 and UK NCRI
RAPID trials
071
Igor Aurer, Zagreb (Croatia)
CALGB 50801 (Alliance): PET adapted therapy in bulky stage I/II classic Hodgkin
lymphoma (cHL).
072
(Continues)
-
23
(Continued)
Tuesday, June 22
Time Session Article/ abstract nr.
Ann S. LaCasce, Boston, MA (USA)
Live Q&A moderated by session chairs
New prognostic score incorporating MTV predicts treatment failure in advanced Hodgkin
Lymphoma
073
Sally F. Barrington, London (UK)
Nivolumab for relapsed or refractory (R/R) classical Hodgkin lymphoma (cHL) after
autologous transplantation: 5‐year overall survival from the phase 2 CheckMate 205
study
074
Stephen M. Ansell, Rochester, MN (USA)
Camidanlumab Tesirine Efficacy and Safety in an Open‐label, Multicenter, Phase 2 Study of
Patients (pts) with Relapsed or Refractory Classical Hodgkin Lymphoma (R/R cHL)
075
Pier Luigi Zinzani, Bologna (Italy)
Live Q&A moderated by session chairs
14:45 – 16:15 Session 12: INDOLENT LYMPHOMAS
Co‐chairs: Astrid Pavlovsky, Buenos Aires (Argentina) and T. Andrew Lister, London (UK)
Intratumoral T‐cells have a Differential Impact on FDG‐PET Parameters in Follicular
Lymphoma
076
Karthik Nath, Brisbane (Australia)
Direct‐acting antivirals as primary treatment for HCV‐associated indolent non‐Hodgkin
Lymphomas: the prospective BArT study of the Fondazione Italiana Linfomi
077
Michele Merli, Varese (Italy)
Primary extranodal follicular lymphoma in a large retrospective survey of the International
Extranodal Lymphoma Study Group (IELSG31)
078
Annarita Conconi, Biella (Italy)
Live Q&A moderated by session chairs
Phase II trial of rituximab plus chlorambucil followed by a 2‐year subcutaneous rituximab
maintenance in MALT lymphoma patients (IELSG38)
079
Maria Cristina Pirosa, Bellinzona (Switzerland)
Response adapted post induction therapy in follicular lymphoma: updated results of the
FOLL12 trial by the Fondazione Italiana Linfomi (FIL).
080
Stefano Luminari, Reggio Emilia (Italy)
Immune Priming with Nivolumab followed by Nivolumab & Rituximab in 1st Line
Treatment of Follicular Lymphoma: The Phase 2 1st FLOR Study
081
Eliza A. Hawkes, Melbourne (Australia)
Live Q&A moderated by session chairs
14:45 – 16:15 Session 13: CAR‐T CELL THERAPY
Co‐chairs: Paolo Corradini, Milan (Italy) and Peter Dreger, Heidelberg (Germany)
CAR‐HEMATOTOX: A discriminative model for CAR T‐cell related hematotoxicity in
relapsed/refractory large B‐cell lymphoma
082
Kai Rejeski, Munich (Germany)
Early PET response predicts outcome in large B‐cell lymphoma patients treated with CD19
CAR‐T
083
Maria Cuadrado, London (UK)
24
-
(Continued)
Tuesday, June 22
Time Session Article/ abstract nr.
First results of DLBCL patients treated with CAR‐T cells and enrolled in DESCAR‐T
registry, a French real‐life database for CAR‐T cells in hematologic malignancies.
084
Steven Le Gouill, Nantes (France)
Live Q&A moderated by session chairs
Efficacy and Safety of Tisagenlecleucel (Tisa‐cel) in Adult Patients (Pts) With Relapsed/
Refractory Follicular Lymphoma (r/r FL): Primary Analysis of the Phase 2 ELARA Trial
085
Nathan H. Fowler, Philadelphia, PA (USA)
TRANSCEND CLL 004: Phase 1 cohort of Lisocabtagene Maraleucel (liso‐cel) combined
with Ibrutinib (ibr) for patients (pts) with R/R CLL/SLL
086
William G. Wierda, Houston, TX (USA)
Outcome of large B‐cell lymphoma patients failing CD19 targeted CAR‐T therapy 087
Andrea Kuhnl, London (UK)
Live Q&A moderated by session chairs
16:30 – 17:00 Special Lecture: Lymphoma Treatment in Developing Countries 088
Chair: Franco Cavalli, Bellinzona (Switzerland)
Andrea Biondi, Monza (Italy)
17:00 – 17:30 Take Home Messages
James O. Armitage, Omaha, NE (USA)
Closure and Farewell
Franco Cavalli, Bellinzona (Switzerland)
-
25
DOI: 10.1002/hon.2879
SUPPLEMENT ABSTRACTS
ORAL PRESENTATIONS
KEYNOTE LECTURES
HENRY KAPLAN MEMORIAL LECTURE
Michael Hallek, Cologne, Germany
001 |TOWARDS CONTROL OF CHRONIC LYMPHOCYTIC
LEUKEMIA WITH TARGETED AGENTS
M. Hallek
1
1
University Hospital of Cologne, Department I of Internal Medicine,
Cologne, Germany
Chronic lymphocytic leukemia (CLL) represents one of the most
active fields of clinical research at the present time.
1,2
This short
review summarizes some of the basic, translational and clinical
research that has led to substantial improvements of the manage-
ment of patients with CLL over the past two decades.
Biology: The use of genetic and genomic technologies has led to an
improved understanding of the biology of CLL. Studies using fluo-
rescent in‐situ hybridization (FISH) and chromosome banding have
described recurrent and frequent aberrations in CLL, some of which,
such as del(17p) have demonstrated profound prognostic impact.
3
Moreover, the mutational composition of immunoglobulin heavy
chain variable region (IGHV) genes separates two apparently related,
but biologically and clinically different forms of CLL.
4,5
These findings
suggested a central role of B‐cell receptor (BCR) signaling in this
leukemia. In a search for the relevant genes disrupted by del(13q),
found in almost 50% of CLL cases, it was discovered that this deletion
causes the loss of miRNAs (miR‐15a and 16‐1), which initiate
leukemogenesis.
6,7
It was suggested that these miRNAs induce the
up‐regulation of Bcl2 protein that is usually highly overexpressed in
CLL.
8
More recently, whole exome sequencing has enabled the
description of the genomic landscape of CLL.
9,10
From these studies
we have learned that genes regulating inflammatory pathways, BCR
signaling and differentiation, Notch signaling, Wnt signaling, DNA
damage control, chromatin modification, RNA and ribosomal pro-
cessing are frequently altered in CLL.
10
Signaling through the BCR seems to play an important role for the
survival of CLL cells.
11
BCR activation in CLL cells induces the activa-
tion of several tyrosine kinases, such as Src family kinases (in particular
LYN), Bruton tyrosine kinase (BTK), Spleen tyrosine kinase (SYK), as
well as phosphoinositide 3‐kinases (PI3K).
12
In addition to BCR
signaling, CLL receive essential growth support through various cell‐
membrane‐bound and soluble factors produced in their cellular
microenvironment.
12
Leukemia associated macrophages are particu-
larly important components of the microenvironment and support the
growth of CLL cells.
13,14
Even the efficacy of conventional therapeutics
such as chemotherapy with alkylators and monoclonal antibodies seem
to mediate their effects through compartment restricted interactions
with macrophages.
15
More recently, we could show that targeted
disruption of BCR associated kinases such as LYN or BTK reduces the
capacity of leukemia‐associated macrophages or fibroblasts to “feed”
CLL growth.
16
Prognosis: The clinical staging systems of Rai or Binet stratify patients
according to their disease‐specific risk. With the new therapies, the
prognostic value of these staging systems has decreased, no longer
differentiating intermediate from advanced stages.
17
A large number
of biomarkers have been identified that provide additional prognostic
information.
18‐20
The most relevant prognostic parameters extracted
from the clinical trials with long follow up are IGHV mutational status,
serum ß
2
‐microglobulin, and the presence of del(17p) and/or TP53
mutations. Usually, high‐risk CLL is defined, at least in part, by genetic
aberrations of the TP53 gene (i.e. del(17p) or TP53 mutations). The
plethora of genetic markers obtained by next generation sequencing
has not yet provided additional prognostic or predictive markers that
are sufficiently validated, and these need to be further tested in clinical
trials.
Using some of these markers, a number of prognostic scores and
stratification systems have been proposed based on multivariate
analyses.
17,21,22
These models are useful to identify high‐risk patient
populations for experimental protocols, but also those patients with a
very good prognosis even at advanced stages. The CLL international
prognostic index (CLL‐IPI) consists of a weighed score that includes
the clinical stage, age, IGHV mutational status, serum ß
2
‐micro-
globulin, and the presence of del(17p) and/or TP53 mutations.
22
It
separates four different prognostic subgroups, and has been vali-
dated extensively. A system for predicting the time to first treatment
(TTFT) in patients with CLL with early, asymptomatic disease was
recently proposed (International Prognostic Score for Early‐stage
CLL [IPS‐E]).
23
Three covariates, unmutated IGHV gene, absolute
lymphocyte count higher than 15 x 10
9
/L, and presence of palpable
lymph nodes were combined and predict a 5‐year cumulative risk for
treatment start of 8.4%, 28.4%, and 61.2% for low‐risk, intermediate‐
© 2021 The Authors. Hematological Oncology published by John Wiley & Sons Ltd.
Hematological Oncology. 2021;39(S2):26–144. wileyonlinelibrary.com/journal/hon
-
26
risk, and high‐risk patients, respectively. The IPS‐E will be helpful to
counsel patients with early stage CLL.
Minimal residual disease: Like in other malignancies, the complete
eradication of the leukemia is an obvious and desired endpoint.
24
At
least three different methods, sensitive multicolor flow cytometry,
PCR, or next‐generation sequencing are able to detect minimal re-
sidual disease (MRD) in CLL patients who otherwise achieve a com-
plete response. Efforts to refine and harmonize these technologies
have established that a typical flow cytometry‐based assay comprises
a core panel of six markers (i.e. CD19, CD20, CD5, CD43, CD79b and
CD81).
25
Patients are defined as having undetectable MRD (MRD‐
neg) remission if they have blood or marrow with less than one CLL
cell per 10.000 leukocytes.
Today, there exists ample evidence from prospective, controlled clin-
ical trials with long‐term follow‐up, that therapies that are able to
achieve MRD‐neg remissions consistently result in a significant
improvement of clinical outcome, including a longer overall survival.
26‐
31
From studies of MRD in patients treated with chemo(immuno)
therapy protocols, we have learned that the assessment of MRD seems
more relevant than the clinical response assessment of CLL to predict
the outcome.
27
The combined use of initial prognostic information, as
provided by the CLL‐IPI and the dynamic assessment of the treatment
response (by MRD assessment) may provide methods to dynamically
determine outcome probabilities for individual patients utilizing risk
predictors acquired over time. The Continuous Individualized Risk
Index (CIRI) shows that in CLL a dynamic risk assessment allows to
accurately predict the outcome following chemoimmunotherapy.
32
Therapy: Chemoimmunotherapy: Progress in CLL therapy has been
initiated by using combinations of purine analogs and cyclophospha-
mide, in particular fludarabine and cyclophosphamide (FC).
33,34
Thereafter, the anti‐CD20 antibody rituximab was added to this FC
chemotherapy backbone (FCR), yielding impressive response rates.
35
Based on these results, the GCLLSG initiated the CLL8 protocol,
comparing FCR to FC. This randomized protocol was the first to show
that the choice of first line therapy, FCR, could improve overall survival
of CLL patients.
36
The benefit of anti‐CD20 antibodies was also shown
for CLL patients with comorbidities using chlorambucil as a standard
comparator arm (CLL11 protocol)
37,38
Interestingly, obinutuzumab, a
more potent type II antibody, yielded a survival benefit when compared
with rituximab. The long‐term follow up of patients treated with FCR
demonstrated that for specific subgroups with a mutated IGHV, del
(13q), trisomy 12 or del(11q), or for those patients achieving a remis-
sion without detectable minimal residual disease (commonly called
MRD‐negative remission).
39‐41
FCR treatment of CLL patients with the
combined occurrence of mutated IGHV genes plus del(13q), del(11q)
or trisomy 12 yielded an overall survival rate above 90% at 5 years.
Together, the lessons learned from these clinical trials were: 1) The
choice of first line therapy in CLL is relevant and changes the natural
history of the disease. 2) We should give our best treatment first. 3)
Anti‐CD20 antibodies are relevant components of CLL therapy. 4)
Long‐term control (or cure) of CLL seems possible.
Targeted agents: More recently, the advent of targeted agents such
as ibrutinib,
42
idelalisib,
43
or venetoclax
44,45
has further improved
the armamentarium of CLL therapies. As it became rapidly apparent
that single agents would not achieve long‐lasting complete re-
missions, we sought to systematically combine different mechanisms
of action rather than testing monotherapy for CLL patients. In the
CLL2‐BAG trial patients received sequential treatment of debulking
with two cycles of bendamustine followed by induction and mainte-
nance with obinutuzumab and venetoclax, yielding very high
response rates of 95%.
46
Therefore, CLL14 protocol investigated a
fixed‐duration treatment with venetoclax and obinutuzumab (VO)
compared with chlorambucil‐obinutuzumab and showed that the
progression‐free survival at 24 months was significantly higher in the
VO group than in the comparator arm (88.2% vs. 64.1).
47
This benefit
was also observed in all major subgroups. Very encouraging results
have also been reported recently regarding the combination of
venetoclax plus ibrutinib.
48,49
Future prospects: We have entered a new era where combinations of
targeted agents achieve long‐lasting remissions for the majority of
CLL patients. In addition, therapy with ibrutinib as a single agents
delivers long‐term disease control, even in high‐risk CLL.
50
Therefore, one of the most important questions regarding CLL
therapy is the comparison of two different treatment concepts, fixed
duration therapy aimed at achieving maximal response (undetectable
MRD) versus long‐term disease control with single agent BTK in-
hibitors. The CLL17 protocol that has just opened recruitment will
address this important question (Figure 1).
Moreover, we need to intensify our effort to understand and
neutralize the cellular mechanism of resistance to the new inhibitors.
FIGURE 1 CLL17 protocol of the German
CLL Study Group
SUPPLEMENT ABSTRACTS
-
27
Finally, and most importantly, we need to make sure that these
novel therapies will become available to all patients with CLL
world‐wide.
Acknowledgements
I wish to thank the patients participating in our trials and members of
the teams at the University of Cologne, and the members and centers
of the German CLL Study group for many years of fruitful coopera-
tion.
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Oncol. 2012;30(9):980‐988.
27. Kovacs G, Robrecht S, Fink AM, et al. Minimal Residual Disease
Assessment Improves Prediction of Outcome in Patients With
Chronic Lymphocytic Leukemia (CLL) Who Achieve Partial
Response: Comprehensive Analysis of Two Phase III Studies of
28
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SUPPLEMENT ABSTRACTS
the German CLL Study Group. J Clin Oncol. 2016;34(31):3758‐
3765.
28. Dreger P, Dohner H, Ritgen M, et al. Allogeneic stem cell
transplantation provides durable disease control in poor‐risk
chronic lymphocytic leukemia: long‐term clinical and MRD re-
sults of the German CLL Study Group CLL3X trial. Blood.
2010;116(14):2438‐2447.
29. Moreton P, Kennedy B, Lucas G, et al. Eradication of Minimal
Residual Disease in B‐Cell Chronic Lymphocytic Leukemia After
Alemtuzumab Therapy Is Associated With Prolonged Survival. J
Clin Oncol. 2005;23:2971‐2979.
30. Wendtner CM, Ritgen M, Schweighofer CD, et al. Consolida-
tion with alemtuzumab in patients with chronic lymphocytic
leukemia (CLL) in first remission‐‐experience on safety and
efficacy within a randomized multicenter phase III trial of the
German CLL Study Group (GCLLSG). Leukemia. 2004;18
(6):1093‐1101.
31. Kwok M, Rawstron AC, Varghese A, et al. Minimal residual dis-
ease is an independent predictor for 10‐year survival in CLL.
Blood. 2016;128(24):2770‐2773.
32. Kurtz DM, Esfahani MS, Scherer F, et al. Dynamic Risk Profiling
Using Serial Tumor Biomarkers for Personalized Outcome Pre-
diction. Cell. 2019;178(3):699‐713 e619.
33. Eichhorst BF, Busch R, Hopfinger G, et al. Fludarabine plus
cyclophosphamide versus fludarabine alone in first line therapy
of younger patients with chronic lymphocytic leukemia. Blood.
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34. Catovsky D, Richards S, Matutes E, et al. Assessment of fludar-
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trial. Lancet. 2007;370(9583):230‐239.
35. Keating MJ, O'Brien S, Albitar M, et al. Early results of a che-
moimmunotherapy regimen of fludarabine, cyclophosphamide,
and rituximab as initial therapy for chronic lymphocytic leuke-
mia. J Clin Oncol. 2005;23(18):4079‐4088.
36. Hallek M, Fischer K, Fingerle‐Rowson G, et al. Addition of rit-
uximab to fludarabine and cyclophosphamide in patients with
chronic lymphocytic leukaemia: a randomised, open‐label, phase
3 trial. Lancet. 2010;376(9747):1164‐1174.
37. Goede V, Fischer K, Busch R, et al. Obinutuzumab plus chlor-
ambucil in patients with CLL and coexisting conditions. N Engl J
Med. 2014;370(12):1101‐1110.
38. Goede V, Fischer K, Engelke A, et al. Obinutuzumab as frontline
treatment of chronic lymphocytic leukemia: updated results of
the CLL11 study. Leukemia. 2015;29(7):1602‐1604.
39. Thompson PA, Tam CS, O'Brien SM, et al. Fludarabine, cyclo-
phosphamide, and rituximab treatment achieves long‐term
disease‐free survival in IGHV‐mutated chronic lymphocytic
leukemia. Blood. 2016;127(3):303‐309.
40. Fischer K, Bahlo J, Fink AM, et al. Long‐term remissions after FCR
chemoimmunotherapy in previously untreated patients with CLL:
updated results of the CLL8 trial. Blood. 2016;127(2):208‐215.
41. Rossi D, Terzi‐di‐Bergamo L, De Paoli L, et al. Molecular pre-
diction of durable remission after first‐line fludarabine‐
cyclophosphamide‐rituximab in chronic lymphocytic leukemia.
Blood. 2015;126(16):1921‐1924.
42. Byrd JC, Furman RR, Coutre SE, et al. Targeting BTK with
ibrutinib in relapsed chronic lymphocytic leukemia. N Engl J Med.
2013;369(1):32‐42.
43. Furman RR, Sharman JP, Coutre SE, et al. Idelalisib and ritux-
imab in relapsed chronic lymphocytic leukemia. N Engl J Med.
2014;370(11):997‐1007.
44. Roberts AW, Davids MS, Pagel JM, et al. Targeting BCL2 with
Venetoclax in Relapsed Chronic Lymphocytic Leukemia. N Engl J
Med. 2016;374(4):311‐322.
45. Stilgenbauer S, Eichhorst B, Schetelig J, et al. Venetoclax in
relapsed or refractory chronic lymphocytic leukaemia with 17p
deletion: a multicentre, open‐label, phase 2 study. Lancet Oncol.
2016;17(6):768‐778.
46. Cramer P, von Tresckow J, Bahlo J, et al. Bendamustine followed
by obinutuzumab and venetoclax in chronic lymphocytic
leukaemia (CLL2‐BAG): primary endpoint analysis of a multi-
centre, open‐label, phase 2 trial. Lancet Oncol. 2018;19(9):1215‐
1228.
47. Fischer K, Al‐Sawaf O, Bahlo J, et al. Venetoclax and Obinutu-
zumab in Patients with CLL and Coexisting Conditions. N Engl J
Med. 2019;380(23):2225‐2236.
48. Jain N, Keating M, Thompson P, et al. Ibrutinib and Venetoclax
for First‐Line Treatment of CLL. N Engl J Med. 2019;380
(22):2095‐2103.
49. Hillmen P, Rawstron AC, Brock K, et al. Ibrutinib Plus Venetoclax
in Relapsed/Refractory Chronic Lymphocytic Leukemia: The
CLARITY Study. J Clin Oncol. 2019;37(30):2722‐2729.
50. Ahn IE, Tian X, Wiestner A. Ibrutinib for Chronic Lymphocytic
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500.
Keywords: Molecular Targeted Therapies, Chronic Lymphocytic
Leukemia (CLL), Combination Therapies
No conflicts of interests pertinent to the abstract.
GIANNI BONADONNA MEMORIAL LECTURE
(in collaboration with American Association for Cancer Research,
AACR)
Ash A. Alizadeh, Stanford, CA, USA
002 |THE ARCHITECTURE OF LIQUID BIOPSY RESEARCH FOR
LYMPHOMA MONITORING
Quantification and qualification of circulating tumor material is an
emerging biomarker of lymphoma that may be used for tumor load
estimation, clonal evolution monitoring, treatment response assess-
ment and early identification of clinically occult relapse. Circulating
SUPPLEMENT ABSTRACTS
-
29
tumor DNA (ctDNA) in blood is an opportunity for comprehensive
and minimally invasive lymphoma diagnostics that is not limited by
sampling frequency, tumor accessibility, or the existence of clinically
overt disease. Qualification of ctDNA is used for the identification of
pre‐treatment mutations associated with primary resistance to
therapy and for the longitudinal non‐invasive detection of acquired‐
resistance mutations under treatment. Quantification of ctDNA is
used as a proxy of imaging for the measurement of tumor volume at
presentation. It allows identifying residual disease after treatment
also when the lymphoma is in complete remission. Persistence of
ctDNA detection during curative‐intent therapy is proposed as dy-
namic prognostic marker for ultimate clinical outcome. Given the
emerging role of the ctDNA, its implementation to detect genomic
variants and residual disease is a priority in the roadmap of lym-
phoma research. Moving ctDNA applications from the bench to the
bedside requires filling the uncertainties surrounding their clinical
validity and, most importantly, clinical utility in the context of pro-
spective clinical trials.
Keywords: Liquid Biopsy, Diagnostic and Prognostic Biomarkers,
Aggressive B‐cell non‐Hodgkin lymphoma
JOHN ULTMANN MEMORIAL LECTURE
(in collaboration with European School of Oncology, ESO)
Stephen M. Ansell, Rochester, MN, USA
003 |IMMUNE SUPPRESSION AND DYSFUNCTION IN THE
TUMOR MICROENVIRONMENT IN LYMPHOMA
S.M. Ansell
1
1
Mayo Clinic Cancer Center, Hematology, Rochester, MN, USA
The tumor microenvironment in lymphoma typically contains sub-
stantial numbers of intratumoral T‐cells suggesting a robust immune
response to malignant B‐cells. It is anticipated that interactions be-
tween antigen presenting cells and immune effector cells result in T‐
cells that are primed to target the malignant clone. However, while T‐
cells are plentiful in the microenvironment of B‐cell malignancies,
they are not able to eradicate the malignancy.
An effective anti‐tumor response requires presentation of tumor
antigens to T‐cells in the context of major histocompatibility
complex proteins, as well as an activating signal resulting in
stimulation of the T‐cell. This results in expansion of a tumor‐
specific T‐cell clone and subsequent generation of cytotoxic pro-
teins that eradicate the malignant cell. To control this process
however, inhibitory receptors are typically upregulated by acti-
vated T‐cells to allow the process to be damped down once the
threat to the host has been contained.
In lymphoid malignancies however, two problems arise. Firstly, ma-
lignant cells commonly overexpress the ligands for inhibitory re-
ceptors. This results in suppression of activated T‐cells expressing
receptors such as PD‐1 and prevents the malignant cell from being
eradicated. This leads to a second problem in that effector T‐cells will
be restimulated by the persistent presence of malignant cells that
express tumor antigens. This repeat stimulation results in immune
exhaustion and upregulation of additional inhibitory receptors such
as TIM3, LAG3 and TIGIT. Cells expressing these receptors have very
little ability to proliferative or generate cytokines despite activation
ex‐vivo.
These observations have therapeutic implications. It is likely that
cells expressing only PD‐1 are activated T‐cells and that the
administration of antibodies that block PD‐1 signaling may protect
these cells from inhibition, allowing them to effectively target tumor
cells. In contrast, PD‐1 positive T‐cells that co‐express receptors
such as TIM3 and LAG3 are typically exhausted and dysfunctional
cells that may not be restored to functional health by simply blocking
PD‐1 signaling. Reactivation of these cells may require blockade of
multiple signaling pathways and some of these cells may not be able
to be functionally restored.
Currently, tumors are often characterized as “inflamed” or “non‐
inflamed” to describe the presence of intratumoral effector T‐cells
and potentially predict responses to immune checkpoint blockade.
A further categorization of “inflamed” lymphomas may be to define
them as “activated” or “exhausted” based on the phenotype of
intratumoral T‐cells. The identification of “activated” rather than
“exhausted” intratumoral T‐cells may potentially be an effective
way of predicting responses to immunotherapy in lymphoma
patients.
Keywords: Immunotherapy, Aggressive B‐cell non‐Hodgkin lym-
phoma, Targeting the Tumor Microenvironment
Conflicts of interests pertinent to the abstract
S. M. Ansell
Research funding: Funding for clinical trials from Bristol Myers
Squibb, Affimed, Trillium, Regeneron, ADC Therapeutics, SeaGen,
Takeda.
PLENARY SESSION
004 |PERVASIVE HYPERMUTATION OF SUPER‐ENHANCER
REGIONS DYSREGULATES ONCOGENE EXPRESSION IN DIFFUSE
LARGE B‐CELL LYMPHOMA
E. Bal
1
, R. Kumar
1
, M. Hadigol
2
, A. Holmes
1
, K. Basso
1
,
H. Khiabanian
2
, L. Pasqualucci
1
, R. Dalla‐Favera
1
1
Columbia University, Institute for Cancer Genetics, the Department of
Pathology and Cell Biology, and the Herbert Irving Comprehensive Cancer
Center, New York, New York, USA,
2
Rutgers University, Center for Systems
and Computational Biology, Rutgers Cancer Institute, New Brunswick,
New Jersey, USA
30
-
SUPPLEMENT ABSTRACTS
Introduction: Diffuse large B‐cell lymphoma (DLBCL) is the most
common B‐cell non‐Hodgkin Lymphoma and remains incurable in
∼40% of patients. Coding‐genome sequencing efforts identified
several genes/pathways altered in this disease, including new po-
tential therapeutic targets. However, the non‐coding genome of
DLBCL remains unexplored. This study was aimed at identifying
functionally relevant non‐coding mutations targeting relevant reg-
ulatory domains such as enhancers (Es) and super‐enhancers (SEs).
Methods: We integrated E/SE identification by ChIP‐seq analysis of
H3K27 acetylation, a histone mark that decorates active regulatory
domains, with whole genome sequencing (WGS) and RNA‐seq anal-
ysis in 29 DLBCL cell lines representative of the major DLBCL sub-
types, along with normal germinal center (GC) B cells representing
the normal counterpart of DLBCL. Ad‐hoc bioinformatics analysis of
WGS data from an extension panel of 93 normal/tumor DLBCL bi-
opsies was then used to nominate recurrently mutated E/SE regions
that were functionally dissected for their specific effect on gene
transcription.
Results: We found that active SEs are highly and specifically
hypermutated (³3 somatic mutations/Kb) in 97% (118/122) of
DLBCL samples analyzed, including cell lines and primary cases, as
compared to the same loci when not active as SE, and to the rest
of the genome (total 135 hypermutated SEs, with at least 2/case).
Such aberrant somatic hypermutation (ASHM) involves both intra‐
genic and inter‐genic SEs, displays signatures of Activation Induced
Deaminase (AID) activity, and is linked to genes encoding B cell
developmental regulators and oncogenes. In order to identify
functional consequences of SE ASHM, we explored the SEs linked
to the BCL6 and BCL2 loci, which were among the most frequently
hypermutated in our panel and have known oncogenic relevance.
In both regions, we identified recurrent ASHM hotspots that were
not mutated in normal GC B cells, and were shown to prevent the
binding of specific transcriptional repressors. Correction of
selected mutations using the CRISPR/Cas9 technology induced
restoration of repressor DNA binding as well as of target gene
transcriptional regulation, and led to counter‐selection of the
corrected alleles, indicating dependency from the ASHM mutations
for tumor cell survival.
Conclusions: These data identify a highly pervasive mutational
mechanism involving regulatory chromatin domains in DLBCL. These
findings: i) reveal a new major set of genetic lesions deregulating
gene expression, including known oncogenes, likely representing an
important mechanism in DLBCL pathogenesis; ii) expand the
involvement of known oncogenes in DLBCL pathogenesis and iden-
tify new deregulated gene targets that may represent candidate
therapeutic targets.
Keywords: Genomics, Epigenomics, and Other ‐Omics,
Aggressive B‐cell non‐Hodgkin lymphoma, Indolent non‐Hodgkin
lymphoma
No conflicts of interests pertinent to the abstract.
005 |EARLY POSITRON EMISSION TOMOGRAPHY RESPONSE‐
ADAPTED TREATMENT IN LOCALIZED DIFFUSE LARGE B‐CELL
LYMPHOMA (AAIPI=0) : RESULTS OF THE PHASE 3 LYSA LNH 09‐
1B TRIAL
S. Bologna
1
, T. Vander Borght
2
, J. Briere
3
, V. Ribrag
4
, G. L. Damaj
5
,
C. Thieblemont
6
, P. Feugier
7
, F. Peyrade
8
, L. Lebras
9
, D. Coso
10
,
D. Sibon
11
, C. Bonnet
12
, F. Morschhauser
13
, H. Ghesquieres
14
,
S. Becker
15
, P. Olivier
16
, B. Fabiani
17
, H. Tilly
18
, C. Haioun
19
,
J. N. Bastie
20
1
Hématologie Privée Nancéienne, 54, Essey lès Nancy, France,
2
Clinique Mont Godine, 5530, Yvoir, Belgium,
3
CHU Henri Mondor,
94, Créteil, France,
4
Institut Gustave Roussy, 94, Villejuif, France,
5
CHU Caen, 14, Caen, France,
6
Hopital Saint Louis, 75, Paris, France,
7
CHRU Nancy, 54, Vandoeuvre lès Nancy, France,
8
Centre Antoine
Lacassagne, 06, Nice, France,
9
Centre Léon Berard, 69, Lyon, France,
10
Institut Paoli Calmette, 13, Marseille, France,
11
Hôpital Necker‐
Enfants Malades, 75, Paris, France,
12
CHU de Liège, 4000, Liege,
Belgium,
13
CHU Lille, 59, Lille, France,
14
Hospices Civils de Lyon, 69,
Lyon, France,
15
Centre Henri Becquerel, 76, Rouen, France,
16
CHRU
Nancy, 54, Vandoeuvre lès Nancy, France,
17
Hopital Saint Antoine,
75, Paris, France,
18
Centre Henry Becquerel, 76, Rouen, France,
19
Hopital Henri Mondor, 94, Créteil, France,
20
CHU Dijon, 21, Dijon,
France
Purpose: R‐CHOP is the standard treatment of diffuse large B‐cell
lymphoma (DLBCL). In localized disease, the FLYER trial (Poeschel
et al., Lancet, 2019) showed that 4 cycles of R‐CHOP‐21 could be
as effective as 6 cycles in the younger population. Several studies
have shown that response assessment by early positron emission
tomography (ePET) was effective to drive treatment for patients
(pts) with DLBCL and aaIPI score ≥1 (Casasnovas et al., Blood,
2017). In the LNH09‐1B trial, using ePET response at central re-
view, we assessed whether 4 cycles of R‐CHOP were non‐inferior
to 6 cycles of R‐CHOP in a limited stage DLBCL patients with
favorable prognosis.
Methods: We performed a randomized trial to evaluate treatment
adaptation on the basis of ePET after 2 cycles of R‐CHOP‐21 in
previously untreated stage I‐II DLBCL pts, aged 18‐80 with aaIPI=0.
The standard arm consisted of 6 cycles of R‐CHOP‐21, regardless of
ePET results. In the experimental arm, ePET‐negative pts received 4
cycles of R‐CHOP‐21 only, whereas ePET‐positive patients received
6 cycles, if second PET performed after 4 cycles showed a complete
metabolic response (defined by a Deauville score ≤3). Progression‐
free survival (PFS) was the primary endpoint. Intention‐to‐treat
(ITT) analysis was used.
Results: From December 2010 to May 2017, we enrolled 650 pts,
331 and 319 in the standard and experimental arms respectively, in
74 centers in France and Belgium. Forty‐four percent of pts were
older than 59 yrs, 4% had a bulky disease (>10 cm), 53% had
extranodal disease (head and neck: 51%, digestive tract: 17%, testis:
SUPPLEMENT ABSTRACTS
-
31
7%, others: 25%). A central histological review was performed for
90.5% of the cases.
With a median follow‐up of 5.1 years (IQR: 3.5‐6.5), 87 pa-
tients (13.4%) had a PFS event. The 3‐yr PFS was 89.2% (95% CI
85.3‐92.2) in the standard arm and 92.0% (95% CI 88.3‐94.5)
in the experimental arm. The non‐inferiority of the experimental
arm versus the standard arm was demonstrated (hazard ratio
0.724, 90% CI 0.504‐1.040, p value from Com‐Nougue test
<0.0001).
Superiority of experimental arm was also tested but was not
observed (one‐sided stratified log‐rank p value=0.0702).
Toxic deaths were very rare, 0 and 1 in the experimental and stan-
dard arms, respectively.
Sixty‐nine patients relapsed with median time of 25.9
months (range, 4.8 to 75.7), suggesting that late relapses may
occurred.
Conclusion: This study demonstrates a non‐inferiority of 4 cycles of
R‐CHOP versus 6 R‐CHOP for early good responders, confirming
that 4 R‐CHOP could be the new standard of care of the large ma-
jority of limited stage DLBCL patients. Occurrence of late relapses
shows the need for long‐term follow‐up for all pts, even if outcome is
very good in this population.
Keywords: Aggressive B‐cell non‐Hodgkin lymphoma, Chemotherapy
No conflicts of interests pertinent to the abstract.
006 |DETERMINANTS OF RESISTANCE TO ENGINEERED T‐
CELL THERAPIES TARGETING CD19 IN LYMPHOMA
B. Sworder
1
, D. M Kurtz
1
, S. Alig
1
, M. J Frank
2
, C. W Macauley
1
,
A. Garofalo
1
, N. Shukla
1
, B. Sahaf
2
, M. S Esfahani
1
, N. Sheybani
1
,
J. Schroers‐Martin
1
, C. L. Liu
1
, M. Olsen
1
, J. Y Spiegel
2
, J. Oak
3
,
M. C Jin
1
, S. Beygi
1
, M. S Khodadoust
1
, Y. Natkunam
3
, R. Majzner
4
,
C. L Mackall
4
, M. Diehn
5
, D. M Miklos
2
, A. A Alizadeh
1
1
Stanford University, Department of Medicine, Division of Oncology,
Palo Alto, California, USA,
2
Stanford University, Department of
Medicine, Division of Blood and Bone Marrow Transplantation, Palo
Alto, California, USA,
3
Stanford University, Department of Pathology,
Palo Alto, California, USA,
4
Stanford University, Department of
Pediatrics, Palo Alto, California, USA,
5
Stanford University, Department
of Radiation Oncology, Palo Alto, California, USA
Introduction: Anti‐CD19 chimeric antigen receptor (CAR19) T‐cells
have activity in patients with relapsed/refractory large B‐cell lym-
phoma (rrLBCL), but over half of patients ultimately relapse. We
applied cell‐free DNA (cfDNA) analysis to patients receiving Axi-
cabtagene Ciloleucel (axi‐cel) to identify determinants of resistance
and characterize molecular thresholds predictive of treatment
failure.
Methods: We developed a novel hybrid‐capture approach allowing
evaluation of both circulating tumor‐derived DNA (ctDNA) and
CAR19‐derived cfDNA (Fig 1A). We applied this to 381 plasma,
FIGURE 1 Progression free survival in the ITT population
32
-
SUPPLEMENT ABSTRACTS
tumor, and germline DNA samples from 64 rrLBCL patients, including
prior to and during treatment and at relapse. We evaluated all
samples for somatic alterations across 246 genes, as well as quanti-
tative levels of ctDNA and CAR19‐cfDNA.
Results: The median follow‐up for the cohort was 12.5 months,
and 55% (35/64) progressed after axi‐cel. We identified 100.5
mutations/case, which was similar to a cohort of 136 untreated
DLBCL patients (P>0.8). Notable differences included more
FIGURE 1 (A) Overview of experimental schema (B) Relationship between CAR19 T‐cell qualification by cfDNA and flow cytometry (C)
Results of univariate cox proportional hazards for EFS for indicated variables. (D) Clonal selection of mutations in specific genes in patients
experiencing relapse shown as a volcano plo. Mutated genes under significant positive selection are shown on the right in red; size of dot
proportional to number of mutations (also shown in parentheses). (E) Left: Recurrently mutated genes in patients receiving axi‐cel therapy,
stratified by progression vs. non‐progression following CAR19 therapy. Right: effect of mutations in given gene on EFS (hazard ration from
proportional hazard model); significant values (P <0.05) shown in green. EFS, event‐free survival; HR, hazard‐ratio; ctDNA, circulating tumor
DNA; cfDNA, cell‐free DNA; CAR19, anti‐CD19 chimeric antigen receptor T‐cell; pre‐lymphodepletion; SNV, single nucleotide variant
SUPPLEMENT ABSTRACTS
-
33
alterations in TP53 (P =0.02), EP300 (P =0.02), SETD1B (P =
0.04), ARID5B (P =0.04), BTK (P =0.04), CD79A (P =0.03), CXCR4
(P =0.03) and RHOA (P =0.03) in rrDLBCL, and fewer alterations
in CD79B (P =0.04) and PIM1 (P =0.03). When considering
ctDNA quantity, both pre‐and on‐treatment levels were prog-
nostic for PFS, with higher levels correlating with adverse outcome
(Pre‐LD [HR =1.5, CI =1.1‐1.9], Day 0 [HR =1.6, CI =1.2‐2.3],
Day +7 [HR =1.5, CI =1.1 – 2.0], Day +28 [HR =1.7, CI =1.4‐
2.2]; Fig 1C). In contrast, higher CAR19‐cfDNA levels at Day +7
were associated with favorable outcome (HR 0.52, CI 0.32‐0.87).
CAR19‐cfDNA was also correlated with CAR19 T‐cell levels by
flow cytometry (Pearson r =0.7, P <0.001; Fig 1B). When we
assessed the effect of specific mutations on outcomes, we
observed recurrent emergence and clonal selection of variants at
relapse, including mutations in CD19,PAX5 and TP53 (Fig 1D).
Finally, mutations in multiple genes were identified as being
prognostic for outcome, including CD58, PAX5 and IRF8 (Fig 1E).
Notably these include both immune‐mediated and target‐mediated
putative mechanisms of resistance. For example, CD58 encodes a
costimulatory T‐cell molecule which has been implicated in CAR19
resistance (Majzner et al., Blood 2020), and PAX5 and IRF8 encode
transcriptional regulatory elements that are central to B‐cell dif-
ferentiation and phenotype.
Conclusions: Baseline and interim ctDNA and CAR19‐cfDNA mea-
surements have prognostic significance in LBCL patients being
treated with CAR19 T‐cells. Additionally, genomic alterations in
several genes, including CD19,CD58, PAX5 and IRF8 are associated
with inferior outcomes, and thus represent candidate resistance
mechanisms that warrant further study with the goal of improving
future generations of CAR T‐cell therapy.
Keywords: Genomics, Epigenomics, and Other ‐Omics, Cellular-
therapies, Liquid biopsy
Conflicts of interests pertinent to the abstract
D. M Kurtz
Consultant or advisory role: Roche, Genentech, Foresight Diagnostics
Stock ownership: Foresight Diagnostics
M. S Khodadoust
Research funding: Corvus Pharmaceuticals
R. Majzner
Consultant or advisory role: Xyphos Inc, Lyell Immunopharma
C. L Mackall
Consultant or advisory role: Lyell, Nektar, PACT, Bryologyx, Vor,
Roche, Adaptimmune, Glaxo‐Smith‐Kline, Allogene, Apricity Health,
Unum Therapeutics
Stock ownership: Lyell, Allogene, Apricity Health, Unum Therapeutics
Research funding: Obsidian
M. Diehn
Consultant or advisory role: Roche, Foresight Diagnostics, Quanticell,
Novartis, Astra Zeneca, BioNTech
Stock ownership: Foresight Diagnostics,
D. M Miklos
Consultant or advisory role: Miltenyi Biotech, Allogene, Kite‐Gilead,
BMS, Celgene, Juno, Novartis, Adaptive Biotechnologies, Precision
Bioscience
Research funding: Becton Dickinson, Kite‐Gilead, Novartis
A. A Alizadeh
Consultant or advisory role: Foresight Diagnostics, Genentech,
Janssen, Pharmacyclics, Gilead, Celgene, Chugai, Roche
Stock ownership: Foresight Diagnostics
Research funding: Pfizer.
AACR‐ICML JOINT SESSION: ARTIFICIAL INTELLI-
GENCE IN LYMPHOMA DIAGNOSIS AND TREATMENT
007 |ARTIFICIAL INTELLIGENCE AND MEDICINE: PAST AND
FUTURE
L.M. Gambardella
1
1
Faculty of Informatics, USI ‐University of Lugano, Lugano
(Switzerland)
The relationship between artificial intelligence and medicine has a
long history. Artificial intelligence initially set out to replicate human
reasoning starting with explicit “if then else” rules. One of the most
interesting results dates back to the 1970s with the MYCIN system
based on a set of 600 rules entered by physicians able to recommend
antibiotic treatments. This direction, although promising, implied a
long input process, a difficult consistency check and was computa-
tionally too heavy. These methodologies have continued over the
years with episodes of small successes and large failures until it was
realized that the way forward was to train artificial systems starting
from real examples, through a methodology called machine learning
and in particular deep learning. The direction was to start from digital
model of the human brain based on artificial neurons, synapses and
axons. Early work involves recognizing of cancer cells from histo-
logical images hand‐annotated by physicians. Artificial neural net-
works are trained showing the artificial neural networks hundreds of
“raw” bit by bit images so that the machine automatically learns how
to identify (sometimes with superhuman performance) cancer cells in
new, unannotated images. The path has then been laid out, with
successful new applications ranging from diagnostics, drug develop-
ment, effects of treatments predicting, patient classification, DNA
analysis, personalized medicine, including robotics for surgery, and
the construction of artificial prostheses to support patients with
disabilities. In this content, it is increasingly important to manage big
34
-
SUPPLEMENT ABSTRACTS
data without forgetting issues of privacy and anonymization. Of great
importance are also new methodologies able to analyze texts and
extract information automatically, thus allowing the integration of
information of different nature and type, but also techniques usefull
to manage uncertainty and lack of data, a phenomenon very often
present in this domain.
In this talk we focus on the recent trends and successes of artificial
intelligence in the medical field, with practical examples in which
artificial intelligence supports physicians in their work, without
forgetting current and future challenges and opportunities, at sci-
entific, application, business but also regulatory level, in an increas-
ingly hybrid world where humans and artificial intelligence will
increasingly interact to improve the quality of life and well‐being of
people.
Keywords: Bioinformatics; Computational and Systems Biology
No conflicts of interests pertinent to the abstract.
008 |ARTIFICIAL INTELLIGENCE AND PATHOLOGY
P. Brousset
1
1
Pathological Anatomy and Cytology, Toulouse University Hospital
Center, Toulouse (France)
The microscopic diagnosis of cancer remains challenging. Recent
data from our group within the French (nationwide) LymphoPath
network shows that 20% of diagnoses are inaccurate, with direct
impact on patient care. Indeed, molecular techniques, that are not
affordable for all pathology departments, have become critical for
the final diagnosis. Currently, automated solutions that could help
pathologists with diagnostic decisions or histological grading are
lacking, and it is not reasonable to expect pathologists to be experts
on rare tumours if they only see a few cases per year. Digital mi-
croscopy offers unique features which are not available in conven-
tional optical microscopy. Assisted by dedicated software tools,
digital microscopy enables dynamic and prompt access to any detail
of the stained slides at several microscopic magnifications. Further-
more, the calibrated qualities and the number of discrete pixels in a
digital slide allow automated image analysis and quantification by
using computer vision and, in particular, deep learning approaches.
Image feature extraction methods based on pixel detection or less
often on object segmentation has brought much hope in improving
the accuracy of the human eye. Automatic analysis of cancer whole‐
slide images has recently been performed to allow experts for pre-
dicting tumour classification, gene mutations and survival outcomes.
However, the positioning of such technologies in routine practice is
limited by the trained networks which frequently do not meet in-
dustrial constraints required for a general application such as certi-
fication, qualification and explainability (black box effect) of
algorithms. This presentation will describe different approaches of
machine learning aiming at classifying cancer subtypes through the
analysis of histopathologic features. Advantages and drawbacks of
these techniques will be discussed with a special emphasis on the
risk of biased performance assessment of deep learning systems. The
critical role of data sets quality will be discussed and different
strategies will be envisaged to broaden the use deep neural net-
works. Providing that these limitations are taken into account and
circumvented, it seems that artificial intelligence solutions dedicated
to cancer histopathology should pave the road to precision medicine
through data integration into a holistic patient dashboard for
oncology care teams.
Keywords: Bioinformatics; Computational and Systems Biology, Ge-
nomics, Epigenomics, and Other ‐Omics, Tumor Biology and
Heterogeneity
Conflicts of interests pertinent to the abstract
P. Brousset
Consultant or advisory role: Roche, MSB, Janssen Cilag laboratory
Research funding: Roche, Pierre Fabre
009 |USE OF DEEP LEARNING TO ANALYSE AND EXPLOIT
MOLECULAR DATA
D.A. Landau
1
1
New York Genome Center, Weill Cornell Medicine, New York, NY, USA
Machine learning holds the promise to transform cancer science and
treatment. The advent of high throughput genomics methods has led
to an explosion of molecular data in cancer. However, to extract
meaningful insights requires advanced machine learning to comb
through the millions of data points and identify key patterns.
Dr. Landau will discuss the application of machine learning to DNA
methylation analysis, describing a novel framework to identify
oncogenic DNA methylation changes. Through this project, Dr.
Landau will review key concepts in ML, including devising appro-
priate background models, developing diagnostics and metrics of
success for methods optimization, and critical factors for building
robust and generalizable prognostic models.
In the second part of the talk, Dr. Landau will discuss the appli-
cation of ML and specifically deep learning to scan through billions
of DNA fragments to identify somatic mutations that can help
detect residual cancer disease in liquid biopsy with ultra‐high
sensitivity.
Keywords: Bioinformatics; Computational and Systems Biology
Conflicts of interests pertinent to the abstract
D. A. Landau
Consultant or advisory role: Mission Bio
Stock ownership: C2i Genomics
Research funding: Illumina, BMS
SUPPLEMENT ABSTRACTS
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35
010 |HOW MACHINE LEARNING CAN ENHANCE CLINICAL
DEVELOPMENT
P. Trichelair
1
1
R&D, Owkin, Paris, France
Deep learning models on medical images are now widely used to cap-
ture signals regarding patients’ outcomes. In this talk, we discuss how
AI models can improve the clinical development pipeline by reducing
the time to market and enhancing prioritization of drugs using external
datasets.
In oncology, both the sample size requirements and the duration are
keys for phase III trials. Recent randomized trials in newly diagnosed
patients with DLBCL have taken on average more than 5 years be-
tween first enrollment and publication [Batlevi2018]. We will present
how this can be reduced by adjusting the primary analysis on deep
learning predictions of the outcome.
Another challenge in clinical development is the decision whether to
launch a phase III trial based on the results of a single‐arm short‐term
phase II trial. This decision process can be enriched by an estimation
of treatment effect based on the single‐arm data and historical
controls. We will discuss how recently developed synthetic control
arm methods, which rely on machine learning, allow more precise
estimation of treatment effect. Additionally, to overcome the short‐
term follow‐up in early phases, we will discuss how digital surro-
gate endpoints, trained on previous phase III trials, can help to
extract information on efficacy.
Keywords: Bioinformatics; Computational and Systems Biology
Conflicts of interests pertinent to the abstract
P. Trichelair
Employment or leadership position in a company: Owkin France
SESSION 1: NEW THERAPEUTICS
011 |TARGETING PROXIMAL BCR SIGNALING PATHWAY IN
DIFFUSE LARGE B‐CELL LYMPHOMA
J. W. Choi
1
, S. Corcoran
1
, B. Wang
1
, Björ. Häupl
2
, M. Ceribelli
3
,
D. W. Huang
1
, G. W Wright
1
, A. L Shaffer III
1
, J. D Phelan
1
,
S. Scheich
1
, X. Yu
1
, Y. Yang
1
, C. Thomas
3
, T. Oellerich
2
, L. M Staudt
1
1
National Cancer Institute, Lymphoid Malignancy Branch, Bethesda,
USA,
2
Goethe University, Department of Medicine II, Hematology/
Oncology, Frankfurt, Germany,
3
National Center for Advancing
Translational Sciences, Division of Preclinical Innovation,
Gaithersburg, USA
Introduction: Stimulation and activation of the B cell receptor
(BCR) signaling propagates multiple proliferative and survival
pathways in normal and malignant B cells. Thus, targeting onco-
genic BCR pathways via pharmacological inhibitions holds promise
and has fundamentally changed the treatment paradigm for B cell
lymphoma patients. Despite the rapid development of BCR
pathway inhibitors and success in treating patients, much work
remains to be done to achieve more effective and long‐lasting
therapies.
Methods: In an effort to identify the new molecular targets in BCR
signaling, a genome wide CRISPR screening in BCR‐dependent
diffuse large B cell lymphoma (DLBCL) was performed. The
signaling networks and interactome of the novel BCR regulator were
assessed by multiplatform ‐omic analysis (quantitative proteomics,
phospho‐proteomics, ubiquitinomics, transcriptomics) and were
validated by flow cytometry and biochemical methods. Furthermore,
CRISPR‐Cas9 drug modifier screening and high‐throughput drug
screening were used to identify synergistic synthetic lethality and
define potential therapeutic drug combinations.
Results: We found that C‐terminal SRC Kinase (CSK) is an
essential gene for BCR‐dependent DLBCL survival. Deletion of
CSK using an inducible CRISPR/Cas9 system decreased cell
viability over time. Expression of CSK (WT) was able to rescue the
toxic effects of CSK deletion while kinase‐dead CSK (K222R)
mutant isoform could not, suggesting that the survival of lym-
phoma cells depends on phosphorylation targets of CSK. CSK in-
hibition by a small molecule inhibitor (CSKi) globally changed the
dynamics of ubiquitylation and phosphorylation of BCR regulators
with the increased BCR signaling output in a short period of time.
However, it ultimately led to the proteasomal degradation of
active and lymphoma specific Src family of protein tyrosine ki-
nases (SFKs), direct targets of CSK, and diminished proximal
BCR signaling. Combinatorial deletion of these SFKs resulted in a
decrease in cell proliferation and survival. Consistently, tran-
scriptomics data revealed that CSK‐inhibited cells show a
reduced downstream survival gene expression when compared to
untreated cells. Lastly, CSKi synergized with BCL2 family in-
hibitors, potentiating the toxicity of CSKi for lymphoma cell line
models.
Conclusion: In summary, we have uncovered that CSK functions as a
positive BCR signaling regulator that sustains active SFKs in the
context of oncogenic BCR signaling. CSK inhibition, by blocking
proximal BCR signaling, represents a novel therapeutic strategy for
aggressive lymphomas that is non‐redundant with existing agents
now used to treat these cancers.
The research was funded by: Intramural Research Program of the
National Institutes of Health, National Cancer Institute, and Center
for Cancer Research
Keywords: Genomics, Epigenomics, and Other ‐Omics, Molecular
Targeted Therapies, Aggressive B‐cell non‐Hodgkin lymphoma
No conflicts of interests pertinent to the abstract.
36
-
SUPPLEMENT ABSTRACTS
012 |MALT1 DEGRADATION FOR THE TREATMENT OF
ACTIVATED B‐CELL TYPE DIFFUSE LARGE B‐CELL LYMPHOMA
M. R. Seshadri
1
, L. Fontán
1
, D. Scott
2
, J. Hatcher
2
, P. Sreevatsan
2
,
G. Du
2
, Q. Qiao
3
, H. Wu
3
, I. Us
1
, M. Xia
1
, N. Gray
4
, A. Melnick
1
1
Weill Cornell Medicine, Department of Medicine, Division of
Hematology and Oncology, New York, New York, USA,
2
Dana Farber
Cancer Institute, Harvard Medical School, Department of Biological
Chemistry and Molecular Pharmacology, Boston, Massachusetts, USA,
3
Boston Children's Hospital, Harvard Medical School, Program in
Cellular and Molecular Medicine, Boston, Massachusetts, USA,
4
Stanford University, Department of Chemical and Systems Biology,
Stanford, California, USA
Introduction: The activated B‐cell (ABC) type of diffuse large B‐
cell lymphoma (DLBCL) is associated with poor response to sec-
ond line therapy and is characterized by constitutive activation of
the NF‐κB pathway. MALT1 is a central signaling molecule which
promotes NF‐κB via dual protease and scaffold functions. Clinical
interest focuses on allosteric MALT1 inhibitors, one of which is
being tested in a phase I trial, however this approach preserves
NF‐κB activation through MALT1 scaffold function. MALT1 pro-
tease is also critical for regulatory T‐cells, raising concern
that protease inhibition alone could cause immune toxicities. We
hypothesize that MALT1 degradation will inhibit NF‐κB more so
than allosteric inhibitors while minimizing autoimmune effects.
We developed several MALT1‐directed proteolysis targeting
chimera (PROTAC) compounds which consist of a MALT1‐binding
domain linked to a cereblon (CRBN)‐binding moiety based on
IMiD drugs such as pomalidomide. CRBN recruitment induces
ubiquitination and proteasomal degradation of MALT1. Structure‐
activity analyses identified a lead compound, PS‐II‐115, for
further study.
Methods: To assess growth inhibition, human ABC‐DLBCL cell lines
(OCI‐Ly3, OCI‐Ly10, TMD8) and germinal center B‐cell (GCB)‐type
DLBCL cell lines (OCI‐Ly1, OCI‐Ly7) were treated with PS‐II‐115 for
96 hours, and CellTiter Glo assay was performed. To assess protein
degradation, cells were treated with PS‐II‐115 5‐10 uM for 23.5
hours followed by vehicle or stimulation with PMA/IO for 30 mi-
nutes, and immunoblots of cell lysates were performed.
Results: PS‐II‐115 induced MALT1 degradation in OCI‐Ly3, an
ABC‐DLBCL cell line dependent on MALT1, and OCI‐Ly1, a GCB‐
DLBCL cell line not dependent on MALT1 (MALT1 degradation
mean ±SEM 73.94 ±9.8% and 53.63 ±4.4% respectively, N =3).
There was no significant degradation of IMiD‐induced CRBN
neosubstrates IKZF1, IKZF3, or GSPT1. PS‐II‐115 caused dose‐
dependent growth inhibition of ABC‐DLBCL cell lines at 96
hours at lower concentrations than in GCB‐DLBCL cell lines,
suggesting the effect is due to MALT1 degradation rather than off‐
target effects (OCI‐Ly3 IC
50
2.54 uM, 95% CI 1.73‐3.80, OCI‐Ly1
IC
50
not reached, N =4). IκB, an inhibitor of NF‐κB which is
degraded following phosphorylation by MALT1‐mediated IKK
recruitment, was detected at a higher level in cells treated with
PS‐II‐115 (IκB 206% compared to vehicle) compared to controls
treated with vehicle or an allosteric MALT1 inhibitor, suggesting
that MALT1 degradation inhibits NF‐κB signaling.
Conclusions: We report a PROTAC compound which induces
potent degradation of MALT1 without degradation of IMiD‐
induced CRBN neosubstrates, associated with selective suppres-
sion of ABC‐DLBCL cell lines and inhibition of the NF‐κB pathway.
Our findings suggest that MALT1 degradation is a promising
strategy for treatment of ABC‐DLBCL and warrants further
development.
Keywords: Molecular Targeted Therapies, Aggressive B‐cell non‐
Hodgkin lymphoma
Conflicts of interests pertinent to the abstract
L. Fontán
Employment or leadership position: Janssen Pharmaceuticals
N. Gray
Consultant or advisory role: Gatekeeper, Syros, Petra, C4, Allorion,
Jengu, B2S, Inception, EoCys and Soltego
Stock ownership: Gatekeeper, Syros, Petra, C4, Allorion, Jengu, B2S,
Inception, EoCys and Soltego
Research funding: Novartis, Takeda, Astellas, Taiho, Jansen, Kinogen,
Her2llc, Deerfield and Sanofi
A. Melnick
Consultant or advisory role: Epizyme, Constellation, KDAC
pharmaceuticals
Research funding: Janssen Pharmaceuticals, Sanofi and Daiichi
Sankyo
013 |KT‐413, A NOVEL IRAKIMID DEGRADER OF IRAK4 AND
IMID SUBSTRATES, HAS A DIFFERENTIATED MOA THAT LEADS
TO SINGLE‐AGENT AND COMBINATION REGRESSIONS IN
MYD88
MT
LYMPHOMA MODELS
M. Mayo
1
, R. Karnik
1
, C. Klaus
1
, K. Sharma
1
, A. McDonald
1
,
D. H Walker
1
, M. Weiss
1
1
Kymera Therapeutics, Research, Watertown, Massachusetts, USA
An important goal of cancer therapy is to improve patient outcomes
by driving to deep and durable tumor responses. The activity of
single‐agent targeted therapies, such as BTK inhibitors or IMiDs
alone, has been modest in relapsed and refractory DLBCL, necessi-
tating the use of combination therapy.
IRAKIMiDs are novel IRAK4 degraders that simultaneously degrade
IMiD substrates and show synergistic antitumor activity over either
mechanism alone, enabling a therapeutically relevant biological
combination within a single small molecule.
SUPPLEMENT ABSTRACTS
-
37
Here we describe KT‐413, a novel IRAKIMiD development candidate.
KT‐413 is a potent and selective degrader of IRAK4 (DC50 6nM) and
IMiD substrates (Ikaros/Aiolos DC50 2nM), that induces rapid and
potent cell killing in MYD88
MT
DLBCL cell lines in vitro. This activity
is superior to both IRAK4‐selective degraders and inhibitors (such as
CA‐4948) and the IMiD CC220, which has similar potency against
IMiD substrates (Ikaros/Aiolos DC50 1 nM). The combined activity of
these two mechanisms drives a synergistic effect on NFkB and IRF4
signaling with greater downstream effect on NFkB, type 1 interferon
(IFN) signaling, apoptosis pathways and cell cycle gene expression
than can be achieved with either CC220 or IRAK4 degraders and
inhibitors alone. These data support the hypothesis that simulta-
neous targeting of both NFkB and type 1 IFN signaling leads to the
rapid antiproliferative and cell killing activity of KT‐413 in MYD88
MT
cells.
In MYD88
MT
DLBCL xenograft models, a single IV dose of KT‐413
showed significant and sustained degradation of both IRAK4 and the
IMiD substrates, Ikaros/Aiolos, supporting the potential for intermit-
tent dosing to drive cell kill and tumor regressions. To assess this, we
have explored the antitumor efficacy of KT‐413 in intermittent dosing
schedules in MYD88
WT
and MYD88
MT
cell line models in vivo. KT‐413
was well tolerated and showed potent antitumor activity in multiple
models of MYD88
MT
DLBCL irrespective of the presence of co‐
mutations in CD79B, TNFAIP3, or IRF4, but substantially lower ac-
tivity in MYD88
WT
models. Regressions were observed on intermit-
tent dosing schedules ranging from QW to Q3W, supporting the
clinical investigation of KT‐413 as monotherapy in patients with
MYD88
MT
DLBCL. KT‐413 also showed strongly additive activity in
combination with rituximab or BTK inhibitors in MYD88
MT
OCI‐Ly10
xenografts in vivo, suggesting the potential for therapeutically rele-
vant drug combinations in MYD88
MT
DLBCL.
Collectively, these data demonstrate the synergistic activity of
combined IRAK4 degradation and IMiD activity with KT‐413 that is
superior to either mechanism alone. Based on these results, we
propose KT‐413 has the potential to be effective both as a single
agent and in combination with other agents in patients with
MYD88
MT
lymphomas.
Keywords: Molecular Targeted Therapies, Aggressive B‐cell non‐
Hodgkin lymphoma
Conflicts of interests pertinent to the abstract
M. Mayo
Employment or leadership position: Kymera Therapeutics
Stock ownership: Kymera Therapeutics
R. Karnik
Employment or leadership position: Kymera Therapeutics
Stock ownership: Kymera Therapeutics
C. Klaus
Employment or leadership position: Kymera Therapeutics
Stock ownership: Kymera Therapeutics
K. Sharma
Employment or leadership position: Kymera Therapeutics
Stock ownership: Kymera Therapeutics
A. McDonald
Employment or leadership position: Kymera Therapeutics
Stock ownership: Kymera Therapeutics
D. H Walker
Employment or leadership position: Kymera Therapeutics
Stock ownership: Kymera Therapeutics
M. Weiss
Employment or leadership position: Kymera Therapeutics
Stock ownership: Kymera Therapeutics
014 |FIRST‐IN‐HUMAN STUDY OF THE EZH1 AND EZH2 DUAL
INHIBITOR VALEMETOSTAT TOSYLATE (DS‐3201b) IN PATIENTS
WITH RELAPSED OR REFRACTORY NON‐HODGKIN
LYMPHOMAS
K. Ishitsuka
1
, K. Izutsu
2
, D. Maruyama
2
, S. Makita
2
, E. D. Jacobsen
3
,
S. Horwitz
4
, S. Kusumoto
5
, P. Allen
6
, P. Porcu
7
, Y. Imaizumi
8
,
N. Yamauchi
9
, S. Morishima
10
, T. Kawamata
11
, F. M. Foss
12
,
A. Utsunomiya
13
, K. Nosaka
14
, G. Serbest
15
, K. Kato
15
, N. Adachi
16
,
K. Tsukasaki
17
, K. Tobinai
2
1
Kagoshima University Hospital, Department of Hematology and
Rheumatology, Kagoshima, Japan,
2
National Cancer Center Hospital,
Department of Hematology, Tokyo, Japan,
3
Dana Farber Cancer
Institute, Department of Medical Oncology, Boston, Massachusetts,
USA,
4
Memorial Sloan Kettering Cancer Center, Department of
Medicine, Lymphoma Service, New York, New York, USA,
5
Nagoya City
University Graduate School of Medical Sciences, Department of
Hematology and Oncology, Nagoya, Japan,
6
Emory University
Winship Cancer Institute, Department of Hematology and Medical
Oncology, Atlanta, Georgia, USA,
7
Sidney Kimmel Cancer Center,
Thomas Jefferson University, Department of Medical Oncology,
Philadelphia, Pennsylvania, USA,
8
Nagasaki University Hospital,
Department of Hematology, Nagasaki, Japan,
9
National Cancer
Center Hospital East, Department of Hematology, Chiba, Japan,
10
University of the Ryukyus Hospital, Department of Hematology and
Oncology, Okinawa, Japan,
11
The Institute of Medical Science, The
University of Tokyo, Department of Hematology, Tokyo, Japan,
12
Yale University School of Medicine, Hematology and Bone
Marrow Transplantation, New Haven, Connecticut, USA,
13
Imamura
General Hospital, Department of Hematology, Kagoshima, Japan,
14
Kumamoto University Hospital, Department of Hematology,
Rheumatology, Infectious Disease, Kumamoto, Japan,
15
Daiichi Sankyo,
Inc, Global Oncology Research & Development, Basking Ridge, New
Jersey, USA,
16
Daiichi Sankyo Co, Ltd, Oncology Medical Science
Department, Tokyo, Japan,
17
Saitama Medical University
38
-
SUPPLEMENT ABSTRACTS
International Medical Center, Department of Hematology, Saitama,
Japan
Introduction: Enhancer of zeste homolog 2 (EZH2) and its
close homolog, EZH1, catalyze the attachment of 3 methyl groups
to histone H3 at lysine 27. Altered EZH2 expression is implicated
in the etiology of non‐Hodgkin lymphomas (NHLs). Valemetostat
tosylate (DS‐3201b; valemetostat) is a novel, potent, and selec-
tive dual inhibitor of EZH2 and EZH1. We report interim results
from a phase 1 trial of valemetostat in patients (pts)
with relapsed or refractory (R/R) NHLs, including peripheral T‐cell
lymphoma (PTCL) and adult T‐cell leukemia/lymphoma (ATL)
(NCT02732275).
Methods: Valemetostat (dose escalation, 150‐300 mg/day; dose
expansion, 200 mg/day) is orally administered once daily in contin-
uous 28‐day cycles to pts with R/R NHL until disease progression or
intolerance. Primary objectives: assess safety and determine recom-
mended phase 2 dose. Secondary objectives included assessing pre-
liminary efficacy.
Results: At data cutoff (November 2, 2020), 78 pts with R/R NHL
were treated; 62 of them with 200 mg. Median follow‐up: 28.1
(range, 3.1‐190.9) wk. Median age: 68 (range, 37‐88) y. Most pts with
NHL (97.4%) experienced ≥1 treatment‐emergent adverse event
(TEAE). Grade ≥3 TEAEs occurred in 51 pts (65.4%); 16 (20.5%) had
serious grade ≥3 TEAEs; no deaths were associated with valemeto-
stat. Dose interruptions or reductions due to TEAEs occurred in 32
(41%) and 7 (9%) pts, respectively. The most common AEs (≥30% of
pts) were platelet count decreased (59.0%), dysgeusia (51.3%), ane-
mia (37.2%), neutrophil count decreased (34.6%), alopecia (32.1%),
and white blood cell count decreased (30.8%). Grade ≥3 platelet
count decreased and thrombocytopenia occurred in 12 (15.4%) and 4
(5.1%) pts. Safety outcomes in PTCL and ATL pts were similar to
those in the overall population.
Preliminary efficacy in 45 pts with R/R PTCL included an overall
response rate (ORR) of 55.6% (95% CI, 40.0%‐70.4%; includes 11
complete responses [CRs] and 14 partial responses [PRs]), me-
dian duration of response (mDOR) of 56.0 (95% CI, 44.43‐not
estimable [NE]) wk, median time to first response (mTTR) of 8.14
(range, 4.1‐24.1) wk, and median progression‐free survival (mPFS)
of 52 (95% CI, 16.14‐NE) wk. Preliminary efficacy in pts with R/R
ATL included an ORR of 50.0% (95% CI, 23.0%‐77.0%; includes 3
CRs and 4 PRs), mDOR that is NE (range 6.14 wk‐NE); mTTR
of 8.14 (range 7.3‐84.1) wk, and mPFS that was NE (95% CI, 8.14
wk‐NE). Efficacy was observed across PTCL subtypes: ORRs in
pts with angioimmunoblastic T‐cell lymphoma, PTCL not other-
wise specified, anaplastic large cell lymphoma, or other T‐cell
lymphomas were 70.6%, 47.6%, 50.0%, and 40.0%, respectively.
Conclusions: Valemetostat showed an acceptable safety profile in pts
with R/R NHLs and encouraging preliminary efficacy in pts with R/R
PTCL or ATL. Valemetostat is being evaluated in a phase 2 study of
pts with R/R ATL in Japan and a global phase 2 study of pts with R/R
PTCL, including R/R ATL.
EA ‐previously submitted to EHA 2021.
The research was funded by: Daiichi Sankyo
Keywords: Aggressive T‐cell non‐Hodgkin lymphoma, Molecular
Targeted Therapies, Ongoing Trials
Conflicts of interests pertinent to the abstract
K. Ishitsuka
Consultant or advisory role: Daiichi Sankyo
Honoraria: Daiichi Sankyo
K. Izutsu
Honoraria: Daiichi Sankyo
Research funding: Daiichi Sankyo
D. Maruyama
Honoraria: Ono Pharmaceutical Co., Ltd, Nippon Shinyaku Co., Ltd,
Celgene KK, Takeda Pharmaceutical Co., Ltd, Janssen Pharmaceutical
KK, Eisai Co., Ltd, Chugai Pharmaceutical Co., Ltd, Kyowa Hakko
Kirin Co., Ltd, Zenyaku Kogyo Co., Ltd, Bristol‐Myers Squibb, Syn-
mosa Biopharma, MSD KK, AstraZeneca KK, Sanofi KK, SymBio
Pharmaceuticals, Ltd, AbbVie GK, Mundipharma KK, Toppan Printing
Co., Ltd
Research funding: Amgen Astellas BioPharma KK, Novartis Pharma
KK, Chugai Pharmaceutical Co., Ltd, Ono Pharmaceutical Co., Ltd,
Takeda Pharmaceutical Co., Ltd, Janssen Pharmaceutical KK, Sanofi
KK, MSD KK, Otsuka, Bristol‐Myers Squibb, Astellas Pharma, Inc,
AbbVie GK, IQVIA Services Japan KK, Celgene KK, Eisai Co., Ltd
S. Makita
Consultant or advisory role: Takeda, Daiichi Sankyo, Celgene
Honoraria: Celgene, Chugai, Eisai, Novartis, Takeda
E. D. Jacobsen
Consultant or advisory role: Hoffmann‐LaRoche, Pharmacyclics,
Acerta, Janssen
S. Horwitz
Consultant or advisory role: Acrotech Biopharma, ADC Therapeutics,
Astex, C4 Therapeutics, Celgene, Janssen, Kura Oncology, Kyowa
Hakko Kirin, Myeloid Therapeutics, ONO Pharmaceuticals, Seattle
Genetics, Takeda, Trillium Therapeutics, Verastem/SecuraBio, and
Vividion Therapeutics
Research funding: ADC Therapeutics, Affimed, Aileron, Cel-
gene, Daiichi Sankyo, Forty‐Seven, Inc., Kyowa Hakko Kirin,
Millennium /Takeda, Seattle Genetics, Trillium Therapeutics, and
Verastem/SecuraBio
S. Kusumoto
Honoraria: Chugai Pharmaceutical Co., Ltd
Research funding: Daiichi Sankyo
P. Allen
Consultant or advisory role: Daiichi Sankyo
Research funding: Kyowa Kirin
SUPPLEMENT ABSTRACTS
-
39
P. Porcu
Consultant or advisory role: Innate Pharma, Viracta, Daiichi Sankyo,
Dren‐Bio, Mundipharma, Telios, Tanabe
Honoraria: Innate Pharma, Viracta, Daiichi Sankyo, Dren‐Bio
Research funding: Innate Pharma, Viracta, Daiichi Sankyo, Servier,
AbbVie, (clinical trial)
Y. Imaizumi
Honoraria: Nippon Shinyaku Co., Ltd, Celgene, SymBio Pharmaceu-
ticals, Sanofi KK, Kyowa Kirin, Eisai, Bristol‐Myers Squibb, Sumitomo
Dainippon Pharma
N. Yamauchi
Consultant or advisory role: Takeda
Research funding: Ono, Celgene, Daiichi Sankyo, Amgen, Genmab
F. M. Foss
Honoraria: Daiichi Sankyo
A. Utsunomiya
Consultant or advisory role: HUYA Japan, JIMRO
Honoraria: Novartis, Kyowa Kirin, Daiichi Sankyo, Bristol‐Myers
Squibb, Celgene, Pfizer, Minophagen, Janssen, Chugai
K. Nosaka
Consultant or advisory role: Kyowa Hakko Kirin
Honoraria: Meiji Seika, Celgene, Eisai, Novartis
Research funding: Kyowa Hakko Kirin, Chugai Pharmaceuticals
G. Serbest
Employment or leadership position: Daiichi Sankyo
K. Kato
Employment or leadership position: Daiichi Sankyo
N. Adachi
Employment or leadership position: Daiichi Sankyo Co., Ltd
Stock ownership: Daiichi Sankyo Co., Ltd
K. Tsukasaki
Consultant or advisory role: Daiichi Sankyo, Ono Pharma, HUYA,
Yakuruto, Meiji Seika Pharma
Honoraria: Celgene, Chugai Pharma, Byer, Eizai, Kyowa Hakko Kirin,
Mundy Pharma, Takeda
Research funding: Daiichi Sankyo, HUYA, Celgene, Chugai Pharma,
Byer, Eizai
K. Tobinai
Consultant or advisory role: Zenyaku Kogyo, Takeda, Mundipharma,
HUYA Bioscience International, Celgene, Ono Pharmaceutical, Daii-
chi Sankyo
Honoraria: Zenyaku Kogyo, Eisai, Takeda, Mundipharma,
HUYA Bioscience International, Kyowa Kirin, Celgene, Chugai
Pharma, Ono Pharmaceutical, Yakult, Daiichi Sankyo, Solasia Pharma
015 |GLOFITAMAB STEP‐UP DOSING: UPDATED EFFICACY
DATA SHOW HIGH COMPLETE RESPONSE RATES IN HEAVILY
PRETREATED RELAPSED/REFRACTORY (R/R) NON‐HODGKIN
LYMPHOMA (NHL) PATIENTS
C. Carlo‐Stella
1
, M. Hutchings
2
, F. C. Offner
3
, F. Morschhauser
4
,
E. Bachy
5
, M. Crump
6
, A. Sureda
7
, G. Iacoboni
8
, C. Haioun
9
, D. Perez‐
Callejo
10
, L. Lundberg
10
, J. Relf
11
, E. Clark
12
, D. Carlile
13
,
E. Piccione
14
, A. Belousov
15
, K. Humphrey
16
, M. J. Dickinson
17
1
Humanitas University and Humanitas Research Hospital, Department
of Biomedical Sciences, Milan, Italy,
2
Rigshospitalet, Department of
Hematology and Phase 1 Unit, Copenhagen, Denmark,
3
Universitair
Ziekenhuis Gent, Department of Hematology, Gent, Belgium,
4
Hôpital
Claude Huriez and Centre Hospitalier Régional Universitaire de Lille,
Department of Hematology, Lille, France,
5
Hospices Civils de Lyon and
Université Claude Bernard, Department of Hematology, Pierre'Bénite,
France,
6
Princess Margaret Hospital, Department of Medical Oncology,
Toronto, Canada,
7
Institut Català d'Oncologia Hospitalet, IDIBELL,
Universitat de Barcelona, Department of Clinical Haematology,
Barcelona, Spain,
8
Vall d’Hebron University Hospital, Department of
Hematology, Barcelona, Spain,
9
Hopital Henri Mondor, AP‐HP,
Lymphoid Malignancies Unit, Créteil, France,
10
F. Hoffmann‐La Roche
Ltd, Clinical Science ‐Product Development Hematology, Basel,
Switzerland,
11
Roche Products Ltd, Clinical Safety ‐Product Develop-
ment Safety, Welwyn Garden City, UK,
12
Roche Products Ltd, Product
Development Biostatistics, Welwyn Garden City, UK,
13
Roche Products
Ltd, Clinical Pharmacology, Pharma Research and Early Development,
Welwyn Garden City, UK,
14
Genentech, Inc., Oncology Biomarker
Development, South San Francisco, USA,
15
F. Hoffmann‐La Roche Ltd,
Product Development Biostatistics, Basel, Switzerland,
16
Roche Products
Ltd, Clinical Science ‐Product Development Hematology, Welwyn
Garden City, UK,
17
The Peter MacCallum Cancer Centre, Royal Mel-
bourne Hospital and The University of Melbourne, Clinical Haematol-
ogy, Melbourne, Australia
Introduction: Glofitamab (RG6026), a T‐cell‐engaging, bispecific, full‐
length antibody, allows bivalent binding to CD20 (B‐cells), and
monovalent binding to CD3 (T‐cells). In NP30179 (NCT03075696),
an ongoing multicenter, Phase I dose‐escalation and expansion study,
0.6–25mg glofitamab fixed‐dosing with obinutuzumab pretreatment
(Gpt), showed high, durable complete responses and manageable
safety in heavily pretreated R/R NHL (Dickinson, et al. EHA 2020).
Glofitamab step‐up dosing (SUD), in addition to Gpt, allowed dose
escalation up to 30mg to maximize efficacy, while mitigating cytokine
release syndrome (CRS) (Hutchings, et al. JCO 2021). We present
updated efficacy data from glofitamab monotherapy SUD cohorts.
Methods: Gpt (1000mg) was given to patients (pts) 7 days pre‐
glofitamab initial dose. Intravenous SUD of glofitamab was given on
Day (D) 1 and 8 of Cycle (C) 1 and then at the target dose from C2D1
(2.5/10/16mg or 2.5/10/30mg); treatment continued for up to 12
cycles, every 21 days. Response rates were based on the Lugano
criteria (Cheson, et al. JCO 2014).
40
-
SUPPLEMENT ABSTRACTS
Results: Fifty‐two pts received glofitamab SUD; 17 and 35 pts
received 2.5/10/16mg and 2.5/10/30mg, respectively. Twenty‐eight
pts (53.8%) had aggressive NHL (aNHL) and 24 pts had indolent
NHL (iNHL). Pts had a median age of 68 (44–85) years and received a
median of 3 (1–12) prior lines of therapy. Forty (76.9%) and 38
(73.1%) pts were refractory to their most recent and any prior CD20
therapy, respectively.
After a median follow‐up of 6.3 months, an updated efficacy analysis
was conducted on December 1, 2020. For pts with aNHL (N =28),
the best overall response (OR) and complete metabolic response
(CMR) rates were 64.3% and 57.1%, respectively; a trend of
improved response was observed with increased target dose, with a
CMR rate of 71.4% at 2.5/10/30mg (N =14). Notably, 4/5 pts (80%)
with mantle cell lymphoma (2.5/10/16mg, n =2; 2.5/10/30mg, n =2)
had CMR. For aNHL, 13/16 CMRs are ongoing, with 8 CMRs lasting
>3 months. For pts with iNHL (N =24), OR and CMR rates were
79.2% and 70.8%, respectively; 14/17 CMRs are ongoing, with 10
CMRs lasting >3 months.
As of August 3, 2020, common adverse events (52 pts) were CRS
(63.5%), neutropenia (38.5%), and pyrexia (32.7%). CRS was mostly
confined to C1: 24/50 pts had CRS after 2.5mg; 20/49 pts after
10mg; 2/16 and 8/32 pts had CRS after 16 and 30mg (C2D1),
respectively. Grade [Gr] 1 and 2 CRS was reported in 18 (34.6%) and
12 (23%) pts, respectively; 3 pts had Gr 3 CRS; none had Gr 4/5
events (ASTCT 2019).
Updated data, including biomarker data on baseline CD20 expression
and CD8 levels in the tumor, will be presented.
Conclusions: Updated data for glofitamab monotherapy SUD show
higher preliminary response rates than previously reported in pts
with R/R NHL who have failed multiple lines of therapy. CRS was
mostly manageable, of low grade, and confined to the first cycle of
treatment.
EA ‐previously submitted to ASCO and EHA 2021.
The research was funded by: F. Hoffmann‐La Roche Ltd. Third‐party
medical writing assistance, under the direction of authors, was pro-
vided by Khalida Rizi, MPharm, PhD, of Ashfield MedComms, an
Ashfield Health company, and was funded by F. Hoffmann‐La
Roche Ltd.
Keywords: Aggressive B‐cell non‐Hodgkin lymphoma,
Immunotherapy
Conflicts of interests pertinent to the abstract
C. Carlo‐Stella
Consultant or advisory role: Sanofi, ADC Therapeutics, F. Hoffmann‐
La Roche Ltd, Karyopharm Therapeutics, Celgene/Bristol‐Myers
Squibb, Incyte
Honoraria: Bristol‐Myers Squibb, Merck Sharp & Dohme, Janssen
Oncology, AstraZeneca, Celgene, Takeda, Incyte, Gilead Sciences
Research funding: ADC Therapeutics, Sanofi, F. Hoffmann‐La
Roche Ltd
Educational grants: F. Hoffmann‐La Roche Ltd, Janssen, Takeda, ADC
Therapeutics
M. Hutchings
Consultant or advisory role: Takeda, F. Hoffmann‐La Roche Ltd,
Genmab
Research funding: Celgene, Genmab, F. Hoffmann‐La Roche Ltd,
Takeda, Novartis
F. Morschhauser
Consultant or advisory role: Bristol‐Myers Squibb, F. Hoffmann‐La
Roche Ltd, Gilead Sciences, Janssen, Servier, Epizyme, Abbvie
Other remuneration: Speakers' bureau: F. Hoffmann‐La Roche Ltd;
Expert testimony: F. Hoffmann‐La Roche Ltd
E. Bachy
Consultant or advisory role: F. Hoffmann‐La Roche Ltd, Incyte
Honoraria: F. Hoffmann‐La Roche Ltd, Janssen, Sanofi, Gilead Sci-
ences, Novartis
M. Crump
Consultant or advisory role: Servier, Gilead Sciences, Novartis Can-
ada Pharmaceuticals Inc.
Honoraria: Gilead Sciences, Servier/Pfizer
Research funding: Roche Canada
A. Sureda
Consultant or advisory role: Takeda, Bristol‐Myers Squibb, Gilead
Sciences, Celgene, Janssen, Novartis
Honoraria: Takeda, Bristol‐Myers Squibb, Merck Sharp & Dohme,
Celgene, Janssen, Sanofi, F. Hoffmann‐La Roche Ltd, Novartis, Gilead
Sciences, Janssen‐Cilag
Other remuneration: Sanofi, Takeda, F. Hoffmann‐La Roche Ltd,
Celgene, Gilead Sciences; Speakers' bureau: Takeda
G. Iacoboni
Consultant or advisory role: Novartis, Celgene/Bristol‐Myers Squibb,
Gilead Sciences
Honoraria: Novartis, Celgene/Bristol‐Myers Squibb, Gilead Sciences,
F. Hoffmann‐La Roche Ltd/Genentech, Inc., Janssen
Educational grants: Novartis, Celgene/Bristol‐Myers Squibb, Gilead
Sciences
C. Haioun
Honoraria: Roche France, Janssen‐Cilag, Gilead Sciences, Miltenyi
Biotec, Amgen, Takeda, Celgene
D. Perez‐Callejo
Employment or leadership position: F. Hoffmann‐La Roche Ltd
Stock ownership: F. Hoffmann‐La Roche Ltd
Honoraria: F. Hoffmann‐La Roche Ltd
L. Lundberg
Employment or leadership position: F. Hoffmann‐La Roche Ltd
Stock ownership: F. Hoffmann‐La Roche Ltd
SUPPLEMENT ABSTRACTS
-
41
J. Relf
Employment or leadership position: Roche Holding AG
Stock ownership: F‐Star Therapeutics, Roche Holding AG, Harpoon
Therapeutics
E. Clark
Employment or leadership position: Roche Products Ltd
D. Carlile
Employment or leadership position: F. Hoffmann‐La Roche Ltd,
AstraZeneca
Stock ownership: F. Hoffmann‐La Roche Ltd, AstraZeneca
E. Piccione
Employment or leadership position: Genentech, Inc.
Stock ownership: F. Hoffmann‐La Roche Ltd
A. Belousov
Employment or leadership position: F. Hoffmann‐La Roche Ltd
K. Humphrey
Employment or leadership position: F. Hoffmann‐La Roche Ltd
Stock ownership: F. Hoffmann‐La Roche Ltd
M. J. Dickinson
Consultant or advisory role: Novartis, Bristol‐Myers Squibb, Gilead
Sciences, F. Hoffmann‐La Roche Ltd, Janssen
Honoraria: F. Hoffmann‐La Roche Ltd, Amgen, Merck Sharp &
Dohme, Janssen, Bristol‐Myers Squibb, Novartis
Research funding: Novartis, F. Hoffmann‐La Roche Ltd, Takeda,
Celgene, Merck Sharp & Dohme
Educational grants: F. Hoffmann‐La Roche Ltd
Other remuneration: Speakers' bureau: Novartis
016 |SUBCUTANEOUS EPCORITAMAB IN PATIENTS WITH
RELAPSED/REFRACTORY B‐CELL NON‐HODGKIN LYMPHOMA:
SAFETY PROFILE AND ANTI‐TUMOR ACTIVITY
M. Hutchings
1
, R. Mous
2
, M. R. Clausen
3
, P. Johnson
4
, K. Linton
5
,
D. J. Lewis
6
, M. E.D. Chamuleau
7
, A. S. Balari
8
, D. Cunningham
9
,
D. DeMarco
10
, K.‐M. Chen
10
, B. Elliott
10
, P. Lugtenburg
11
1
Rigshospitalet, Copenhagen University Hospital, Department of
Hematology, Copenhagen, Denmark,
2
On behalf of the Lunenburg
Lymphoma Phase I/II Consortium‐HOVON/LLPC, Universitair Medisch
Centrum Utrecht, Department of Hematology, Utrecht, Netherlands,
3
Vejle Hospital, Department of Hematology, Veile, Denmark,
4
Cancer
Research UK, Cancer Services, University of Southampton, Department of
Hematology, Southampton, UK,
5
Christie Hospital NHS Foundation Trust,
Division of Cancer Services, Manchester, UK,
6
Plymouth University
Medical School, Department of Hematology, Plymouth, UK,
7
On behalf of
the Lunenburg Lymphoma Phase I/II Consortium‐HOVON/LLPC, VU
University Medical Center, Department of Hematology, Amsterdam,
Netherlands,
8
Institut Català d'Oncologia‐Hospital Duran i Reynals,
Hospitalet del Llobregat, Department of Hematology, Barcelona, Spain,
9
The Royal Marsden NHS Foundation Trust, Department of Hematology,
Sutton, UK,
10
Genmab, Clinical Research and Development, Princeton,
New Jersey, USA,
11
On behalf of the Lunenburg Lymphoma Phase I/II
Consortium‐HOVON/LLPC, Erasmus MC Cancer Institute, Department of
Hematology, Rotterdam, Netherlands
Introduction: Epcoritamab is a CD20xCD3 bispecific antibody that
induces T‐cell–mediated killing of CD20–positive malignant B‐cells.
We present updated data, including progression‐free survival (PFS)
from the dose escalation part of the first‐in‐human phase 1/2 study
of epcoritamab in patients with relapsed or refractory (R/R) B‐cell
non‐Hodgkin lymphoma (B‐NHL; NCT03625037).
Methods: Adults with R/R CD20+B‐NHL received flat‐dose 1 mL SC
epcoritamab (step‐up dosing approach) in 28‐day cycles (q1w: cycles
1–2; q2w: cycles 3–6; q4w thereafter) until disease progression or
unacceptable toxicity. Step‐up dosing and standard prophylaxis were
used to mitigate severity of cytokine release syndrome (CRS).
Results: At data cut off (1/31/21), 68 patients with B‐NHL were
enrolled across histologies including diffuse large B‐cell lymphoma
(DLBCL; n =46 [67.6%]; de novo and transformed), follicular lym-
phoma (FL; 12 [17.6%]), mantle cell lymphoma (MCL; 4 [5.9%]), and
others (6 [8.8%]). Most patients were heavily pretreated (median
[range] prior lines: DLBCL, 3 [1–6]; FL, 4.5 [1–18]), including prior
CAR‐T (n =6) and prior ASCT (n =10). At median follow‐up of 14.1
months (DLBCL, 10.2 months; FL, 15.2 months), treatment was
ongoing in 15 (22%) patients. The most common treatment‐emergent
adverse events (AEs) were pyrexia (69%), CRS (59%), and injection
site reaction (47%). CRS events were all grade 1 or 2 and most
occurred in cycle 1; neurotoxicity was limited (6%; grade 1: 3%; grade
3: 3%; all transient). One case of tumor lysis syndrome was observed
(1.5%; grade 3); there were no cases of febrile neutropenia or
treatment‐related death. Overall response rates (ORRs) for patients
with DLBCL at doses ≥12 mg (n =22) and ≥48 mg (n =11) were 68%
(CR =46%; PR =23%) and 91% (CR =55%; PR =36%), respectively.
ORR for patients with FL at doses ≥12 mg (n =5) was 80% (CR =
60%; PR =20%); ORR for patients with MCL at doses ≥0.76 mg (n
=4) was 50% (CR =25%; PR =25%). Responses deepened over
time (PR converted to CR: DLBCL, 6 patients; FL, 3 patients). For
patients with DLBCL, median time to response was 1.4 months;
median time to CR was 2.7 months. For patients with FL, median
time to response was 1.9 months. Among DLBCL patients
achieving CR with doses ≥6 mg (n =11), none relapsed while on
treatment. The median PFS for patients with DLBCL ≥12 mg (n =
22) was 9.1 months (95% CI: 1.6, NE; median follow‐up 9.3
months) and for patients with DLBCL ≥48 mg (n =11) median PFS
was not reached (median follow‐up 8.8 months) (Figure). Updated
analyses will be presented.
Conclusions: With longer follow‐up, SC epcoritamab demonstrated
substantial single‐agent activity, inducing deep and durable clinically
meaningful responses, with a consistent safety profile. Notably no
severe (grade ≥3) CRS events, no febrile neutropenia, and limited
neurotoxicity was observed.
42
-
SUPPLEMENT ABSTRACTS
EA ‐previously submitted to EHA 2021.
The research was funded by: Genmab A/S and AbbVie Inc.
Keywords: Aggressive B‐cell non‐Hodgkin lymphoma
Conflicts of interests pertinent to the abstract
M. Hutchings
Research funding: Genmab, Roche, Takeda, Novartis, Incyte
M. R. Clausen
Consultant or advisory role: Janssen, AbbVie, Gilead
Educational grants: AbbVie, Gilead
P. Johnson
Other remuneration: Genmab
D. Cunningham
Consultant or advisory role: OVIBIO
Other remuneration: Amgen, Sanofi, Merrimack, AstraZeneca, Cel-
gene, MedImmune, Bayer, 4SC, Clovis, Eli Lilly, Janssen, Merck
D. DeMarco
Employment or leadership position: Genmab
K.‐M. Chen
Employment or leadership position: Genmab
B. Elliott
Employment or leadership position: Genmab
P. Lugtenburg
Other remuneration: Takeda, Servier, Roche, Genmab, Celgene,
Regeneron, Incyte
SESSION 2: LYMPHOMA IMAGING
017 |DEFINING ULTRA‐HIGH‐RISK DLBCL PATIENTS
PRIOR TO INITIAL TREATMENT BASED ON AN INTEGRATIVE
HOST AND DISEASE PROGNOSTIC SCORE (FROM REMARC
STUDY)
C. Thieblemont
1
, J.‐F. Deux
2
, L. Vercellino
3
, L. Chartier
4
,
O. Casasnovas
5
, A. Judet
1
, V. Baud
6
, Hervé Tilly
7
, A.‐S. Cottereau
8
,
M. Meignan
9
1
APHP, Saint‐Louis Hospital, Hemato‐oncology, Paris, France,
2
APHP,
Hopital Henri Mondor, Radiology, Paris, France,
3
APHP, Hopital Saint‐
Louis, Medecine Nucleaire, Paris, France,
4
LYSARC, Statistique, Pierre‐
Bénite, France,
5
CHU le Bocage, Hematologie, Dijon, France,
6
Université
de Paris, NF‐KappaB, différenciaation et Cancer, Paris, France,
7
Centre
Henri Becquerel, INSERM U1245, Rouen, France,
8
APHP, Hopital
Cochin, Medecine Nucleaire, Paris, France,
9
LYSA‐IM, Hopital Henri
Mondor, LYSA‐IM, Paris, France
Background: The risk stratification of patients (pts) with
diffuse large B‐cell lymphoma (DLBCL) is based on the widely
used IPI. Three of the IPI variables (LDH, stage and number of EN
sites) may be refined in two metabolic measures obtained by
18FDG‐PET, the total metabolic tumor volume (TMTV) and the
SUPPLEMENT ABSTRACTS
-
43
TABLE 1Hazard ratio (HR) and p‐
value considering ECOG PS and TMTV,
SDmax, LSAD for PFS and OS
Parameter estimate for score
PFS OS
HR 95%CI p‐value HR 95%CI p‐value
ECOG>=2, 0.57 1.77 1.0‐3.0 0.0359 1.95 1.0‐3.6 0.0349
DMAX>32m
‐1
0.76 2.13 1.3‐3.4 0.0013 1.57 0.88‐2.8 0.13
LSAD>–90HU 0.70 2.01 1.3‐3.2 0.0033 2.06 1.2‐3.7 0.0152
TMTV>220cm
3
0.59 1.81 1.1‐3.0 0.0171 2.72 1.4‐5.4 0.0042
FIGURE 1 Progreesion‐free survival and overall survival according to the IPI, the NCCN IPI and the MVED
2
score
44
-
SUPPLEMENT ABSTRACTS
distance between 2 lesions (SDmax). We recently demonstrated
that the adipose tissue alteration measured by the lumbar subcu-
taneous adipose density (LSAD) (i.e an increased density) is an
independent prognostic parameter in DLBCL. The aim was to
analyze if these combined parameters characterizing the host
(ECOG PS) and the disease (TMTV, SDmax, LSAD) could help to
better identify patients at high risk of relapse, prior to initial
treatment.
Patients and Methods: Pts were included in the REMARC study
(NCT01122472), (DLBCL >60 to 80 years old, responder to R‐CHOP
randomized between lenalidomide or placebo). TMTV, SDmax, LSAD
were measured on the baseline PET/CT performed before treatment.
Statistical methods included multiple Cox regression for developing
the MVE2D score.
Results: 273 pts were analyzed. 195 (71%) pts were scored high‐risk
(3‐5) IPI, and 155 (57%) high‐intermediate‐risk NCCN IPI and 36
(13%) high‐risk NCCN IPI. ECOG PS and TMTV, SDmax, LSAD were
identified as the 4 independent prognostic factors for PFS and OS
(Table 1).
Accordingly, a score Metabolic Volume ECOG Distance
Density (MVED
2
) was calculated as 0.57 (if ECOG PS ≥2) +
0.76 (if SDMAX >32) +0.70 (if LSAD > −90) +0.59 (if
TMTV>220).
According to the MVED
2
score, pts were classified into low risk (65%
of pts, median PFS and OS of 68 months and not reached, respec-
tively), intermediate risk (25% of pts, median PFS and OS of 60
months and not reached, respectively) and high risk (10% of pts,
median PFS and OS of 16 and 44 months, respectively) (Fig 1). The
MVED
2
score has a significant impact on PFS (p <0.001) and OS (p <
0.001) (Figure 1). More extra‐nodal sites (89.3% >1 vs 47.3%, p <
0.001), more high‐IPI 3‐5 (96.4% vs 68.6%, p =0.001), more high‐
NCCN IPI (35.7% vs 10.6%, p <0.001), more ABC profile (46.4% vs
20.8%, p =0.033), more involved bone marrow biopsy (42.9% vs
14.7%, p <0.001) and male sex (78.6% vs 58%, p =0.041) were
observed in high risk patients than in the low‐and intermediate‐risk
patients.
Conclusions: The MVED
2
is the first prognostic index based on
new metrics measured on 18FDG‐PET and ECOG PS that may
help to discriminate ultra high‐risk DLBCL pts, even responder to
R‐CHOP.
Keywords: Diagnostic and Prognostic Biomarkers
Conflicts of interests pertinent to the abstract
C. Thieblemont
Consultant or advisory role: BMS, Novartis, Kyte/Gilead, Roche,
Incyte
Honoraria: BMS, Novartis, Kyte/Gilead, Roche, Incyte
018 |INTEGRATION OF BASELINE METABOLIC PARAMETERS
AND MUTATIONAL PROFILE PREDICTS OUTCOME IN DLBCL
PATIENTS. A POST HOC ANALYSIS OF SAKK38/07 STUDY
S. Genta
1
G. Ghilardi
2
, L. Cascione
3
, D. Juskevicius
4
, A. Tzankov
4
,
S. Schär
5
, L. Giovanella
6
, S. Hayoz
5
, C. Mamot
7
, S. Dirnhofer
4
,
E. Zucca
1
, L. Ceriani
6
1
Oncology Institute of Southern Switzerland, Clinic of Medical Oncology,
Bellinzona, Switzerland,
2
Oncology Institute of Southern Switzerland,
Clinic of Hematology, Bellinzona, Switzerland,
3
Università della Svizzera
Italiana, Institute of Oncology Research, Faculty of Biomedical Sciences,
Bellinzona, Switzerland,
4
University Hospital Basel, University of Basel,
Institute of Medical Genetics and Pathology, Basel, Switzerland,
5
Swiss
Group for Clinical Cancer Research (SAKK) Coordinating Center,
Coordinating Center, Bern, Switzerland,
6
Imaging Institute of Southern
Switzerland, Ente Ospedaliero Cantonale, Clinic of Nuclear Medicine and
PET/CT Center, Bellinzona, Switzerland,
7
Cantonal Hospital Aarau,
Division of Oncology, Aarau, Switzerland
Background: Metabolic tumor volume (MTV), metabolic heteroge-
neity (MH) and other functional parameters from baseline (18)F‐
fluorodeoxyglucose positron emission tomography (PET)/computed
tomography (CT), combined with gene expression and mutational
profiles could be useful to predict the risk of treatment failure in
diffuse large B‐cell lymphoma (DLBCL). Nevertheless, so far, prog-
nostic algorithms integrating measurable PET/CT parameters and
genetic information have not been proposed.
Methods: In the clinical study SAKK38/07 (NCT00544219) of the
Swiss Group for Clinical Cancer Research (SAKK), 141 DLBCL patients
received R‐CHOP14 immunochemotherapy (rituximab, cyclophos-
phamide, doxorubicin, vincristine and prednisone every 2 weeks).
Targeted high‐throughput sequencing on tumor genomic DNA was
performed on either all exons or hotspots of 68 genes frequently
mutated in B‐cell lymphomas. The measurement of baseline MTV and
MH PET/CT was combined with the mutational profiles in order to
explore whether this may allow a better prognostication.
Results: Mutational profiles were available for 72 (51%) patients. The
presence of mutations of SOCS1, without mutations in CREBBP and
EP300, defined a group of patients with favorable prognosis with a 5‐
year progression‐free survival (PFS) rate of 100%, while patients
harboring mutations in CREBBP or EP300 or with SOCS1 wild‐type
had a 5‐year PFS of 69% (p =0.025).
Using an unsupervised recursive partitioning approach, we generated
a decision‐tree algorithm, stratifying patients at each step according
to the characteristic with the greater capability to predict PFS
(Figure 1A). MTV with a cut‐off at 9311mL was the factor with the
highest correlation with PFS. Among patients with high MTV, the
presence of MH higher than 0.43 AUC‐CSH defined a high risk group
(N =21; 15%). Among patients with low MTV, the presence of
SUPPLEMENT ABSTRACTS
-
45
46
-
SUPPLEMENT ABSTRACTS
favorable mutational profile identified a low risk group (N =12; 9%).
The remaining patients, namely high MTV and low MH, and low MTV
without favorable mutation profile were merged in an intermediate
risk group (N =108; 76%).
The resulted combined genetic profile/metabolic response model was
able to stratify patients according to PFS, with 2‐year PFS of 100% in
the low risk, 82% in the intermediate risk and 42% in the high risk
group, respectively (p <0.001) (Figure 1B). The positive predictive
power of the model was 57%, while the negative predictive power
was 100%.
Conclusions: This study suggests that the integration of functional
PET/CT parameters and mutational profiles in prognostic models may
enable a more accurate definition of individual DLBCL patient's risk.
Future studies with broader mutational panels and validation in in-
dependent datasets are warranted. If confirmed, these results may
potentially provide a valid tool for dynamically optimizing therapeutic
strategies in DLBCL patients.
Keywords: Diagnostic and Prognostic Biomarkers, PET‐CT, Aggres-
sive B‐cell non‐Hodgkin lymphoma
No conflicts of interests pertinent to the abstract.
019 |BASELINE METABOLIC TUMOR VOLUME AND IPS
PREDICT ABVD FAILURE IN ADVANCED‐STAGE HODGKIN
LYMPHOMA WITH A NEGATIVE INTERIM PET SCAN AFTER 2
CHEMOTHERAPY CYCLES. A RETROSPECTIVE ANALYSIS FROM
THE GITIL/FIL HD0607 TRIAL
A. Gallamini
1
, A. Rambaldi
2
, C. Patti
3
, A. Romano
4
, S. Viviani
5
,
S. Bolis
6
, S. Oppi
7
, L. Trentin
8
, M. Cantonetti
9
, R. Sorasio
10
,
P. Gavarotti
11
, D. Gottardi
12
, C. Schiavotto
13
, R. Battistini
14
,
G. Gini
15
, Andrès Ferreri
16
, C. Pavoni
2
, F. Bergesio
17
, U. Ficola
18
,
L. Guerra
19
, S. Chauvie
17
1
Antoine Lacassagne Cancer Center, Research and Clinical Innovation,
Nice, France,
2
Ospedale Papa Giovanni XXIII, Hematology, Bergamo,
Italy,
3
Ospedali Riuniti di Palermo, Hematology, Palermo, Italy,
4
Policlinico Universitario A. Ferrarotto, Hematology, Catania, Italy,
5
Istituto Europeo di Ematologia, Hematology, Milano, Italy,
6
Ospedale
S. Gerardo, Hematology, Monza, Italy,
7
Ospedale Antonio Businco,
Hematology, Cagliari, Italy,
8
Azienda Ospedaliera di Padova,
Hematology, Padova, Italy,
9
Policlinico Tor Vergata, Hematology, Roma,
Italy,
10
Ospedale S. Croce e Carle, Hematology, Cuneo, Italy,
11
Ospedale S. Giovanni Battista, Hematology ‐University, Torino, Italy,
12
Ospedale Mauriziano, Hematology, Torino, Italy,
13
Ospedale S.
Bortolo, Hematology, Vicenza, Italy,
14
Ospedale S. Camillo Forlanini,
Hematology, Roma, Italy,
15
Ospedali Riuniti di Ancona, Hematology,
Ancona, Italy,
16
S. Raffaele Hospital, Hematology, Milano, Italy,
17
Ospedale S. Croce e Carle, Medical Physics, Cuneo, Italy,
18
Ospedale
La Maddalena, Nuclear Medicine, Palermo, Italy,
19
Ospedale S. Gerardo,
Nuclear Medicine, Monza, Italy
Background: Interim PET performed after 2 chemotherapy cy-
cles (PET‐2) proved the most powerful predictor of ABVD outcome
in advanced‐stage (as) classical Hodgkin lymphoma (cHL). However,
in four prospective clinical trials, the 3‐Y PFS of as‐cHL pa-
tients (p.) with a negative PET‐2 treated with 6 ABVD cycles,
proved deceivingly low, ranging between 79% to 87%, even
declining to 76% after a 5‐year follow‐up (Stephens 2019). To-
tal Metabolic Tumor Volume assessed in the baseline PET
(bTMTV) proved a powerful predictor of treatment outcome in
early stage cHL (Cottereau 2018). We report here the predictive
value of bTMTV on ABVD outcome in as‐cHL p. with a negative
PET‐2.
Patients and methods: 783 as‐CHL (IIB‐IVB) p. were included in the
HD0607 clinical trial (NCT00795613). 630 of them (81%) with both a
negative PET after 2 and 6 ABVD cycles were randomly assigned to
no further therapy (NFT) or consolidation radiotherapy (cRT) in the
area where a nodal mass with a diameter ≥5 cm. was recorded at
baseline. Baseline PET was available in 331 (52%) p. for bTMTV
computing. bTMTV was calculated adopting a relative threshold of
41% SUVmax.
Results: The demographics of the 331 p. included in the bTMTV
study and of the overall cohort of 630 PET‐2 negative p. were:
median age 31 (14‐60) Vs. 31 (14‐60), M/F ratio 0.86 Vs. 0.89;
WHO Performance Status 0‐: 91.5 Vs. 91.4%; >1; B‐symptoms:
81.8 Vs. 81.1%; Stage IIB, III and IV: 35.0, 35.0, 29.9, Vs.36.3, 33.0
and 30.0%; IPS 0‐1 39.3 Vs. 39.8%, IPS 2‐3 48.3 Vs. 49.4%, IPS >3
12.4 Vs. 10.6%, Bulky 18.1 Vs. 17.9%. No difference in 6‐y
PFS was recently reported for p. randomized to NFT or cRT (p
=0.48; Gallamini 2020). The median TMTV value assessed with a
41% SUVmax threshold in the cohort of 331 p. was 138 (3‐1228)
ml. In the ROC analysis, the most accurate TMTV value to predict
the long‐term ABVD outcome in terms of 3‐Y PFS was 471 ml
(AUC =0.61; 95% CI 0.51 – 0.68). After a median follow‐up of
40.6 (4.8‐87.2) months the 3‐Y PFS for the 331 p. included in the
present analysis and for all the 630 PET‐2 negative ones was 84%
(95% CI 81 – 87) and 87% (95% CI, 84% to 89%), respectively.
Treatment failure was recorded in 51/331 (15.4%) and 81/627
(12.9%), respectively. In multivariate analysis no single variable had
a statistically significant predictive value and the Cox model
had an AUC of 0.68 (95% CI 0.60‐0.76) to discriminate high Vs.
low risk population. Upon combining IPS and TMTV, we were
able to single out three distinct cohorts of p. with a different
treatment outcome (p =0.0002): (1) p. with both low TMTV and
IPS (0‐1): 3‐Y PFS 0.98 (95% CI 0.93 – 1.00) (N =23: 7%);
(2) p. with low TMTV and high IPS (>1): 3‐Y PFS 0.85 (95% CI
0.81‐0.90) (N =263: 80%); (3) p. with a high TMTV and high IPS(>
1): 3‐Y PFS 0.56 (95% CI 0.39‐0.81) (N =43: (13%). Conclusions:
IPS and bTMTV >471 ml. proved able to identify a p. subset
that, despite a negative PET‐2, failed ABVD treatment,
thus deserving an alternative and more aggressive frontline
treatment.
SUPPLEMENT ABSTRACTS
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47
Keywords: PET‐CT
No conflicts of interests pertinent to the abstract.
020 |PROGNOSTIC ROLE OF LESION DISSEMINATION
FEATURE (DMAX) CALCULATED ON BASELINE PET/CT IN
HODGKIN LYMPHOMA
R. Durmo
1
, A. Ségolèn. Cottereau
2
, L. Rebaud
3
, C. Nioche
3
,
A. Ruffini
4
, F. Fioroni
5
, M. Meignan
6
, I. Buvat
3
, F. Merli
7
,
A. Versari
8
, S. Luminari
7
1
University of Modena and Reggio Emilia, PhD program in Clinical and
Experimental Medicine (CEM), Modena, Italy,
2
Cochin Hospital, AP‐HP,
University of Paris, Department of Nuclear Medicine, Paris, France,
3
UMR 1288 Université Paris Saclay/Inserm/Institut Curie, LITO labo-
ratory, Orsay, France,
4
Grade Onlus, Hematology Unit, Reggio Emilia,
Italy,
5
AUSL‐IRCCS of Reggio Emilia, Medical Physics, Reggio Emilia,
Italy,
6
Henri Mondor University Hospital, AP‐HP, University Paris East,
Lusa Imaging, Creteil, France,
7
AUSL‐IRCCS of Reggio Emilia, Hema-
tology Unit, Reggio Emilia, Italy,
8
AUSL‐IRCCS of Reggio Emilia, Nu-
clear Medicine, Reggio Emilia, Italy
Aim/Introduction: A non negligible number of patients with
Hodgkin Lymphoma (cHL) experience disease relapse requiring
salvage therapies. Identifying these relapsing or refractory patients
is very important to improve risk stratification and individualize
treatment. Recently, the largest distance between two lesions
(Dmax) measured from FDG PET scans and reflecting lesions
dissemination, has been identified as a new prognostic factor in
diffuse large B cell lymphoma. The aim of this study was to
investigate the prognostic value of Dmax in newly diagnosed cHL
patients and to define interaction of Dmax with other available
prognostic factors.
Materials and Methods: We selected a retrospective cohort of pa-
tients treated between 2007‐2020. Available baseline FDG‐PET scan
for review and clinical data were required for inclusion. From the
baseline PET images all lesions were semiautomatically segmented.
The centroid of each lesion was automatically obtained and consid-
ered as the lesion location. The distances between all pairs of lesions
were calculated and Dmax was obtained for each patient. Dmax was
dichotomized according to the median value within our cohort. Early
metabolic response (iPET) was also reviewed when possible and re-
ported according to the five‐point Deauville scale (DS). Main study
endpoint was Progression Free Survival (PFS).
Results: We identified a study population of 215 cHL patients. Me-
dian age was 39 (15‐88), 43% were younger that 45 years and 45%
had stage III‐IV. Dmax was calculated in 184/215 patients, median
value was 21cm (range 2.6‐78). iPET was available in 187/215 pa-
tients and was positive in 34 cases (DS4‐5; 18%). 42% had a IPS score
more than 2. Higher DMAX values were observed for males, for
patients with low serum albumin, low LDH, elevated ESR, and high
MTV. Median follow up was 38 months and 5year PFS was 77% (95%
48
-
SUPPLEMENT ABSTRACTS
CI 70‐82%). In univariate analysis, IPS>2 (HR 2.20 CI 1.26‐3.87, p =
0.006), iPET+(HR 3.32 CI 1.73‐6.39, p <0.001) and Dmax>20 (HR
2.42 CI 1.31‐4.47, p =0.005): were associated with shorter PFS.
Combining DMAX with iPET we were able to show a meaningful role
of DMAX in the identification of patients at different risk of pro-
gression among iPET‐cases. Using iPET‐and DMAX <20cm as
reference groups the iPET‐and Dmax >20 had a HR of 4.16 (95% CI
1.54‐11.2), and iPET+had a HR of 6.13 (95% IC 2.18‐17.2 ) (Figure 1)
Conclusion: Dmax, a PET feature reflecting the spread of the disease,
is a promising prognostic factor in cHL. Combining Dmax and iPET
further improves risk stratification of patients with HL and might
improve tailored therapy approach.
Keywords: Diagnostic and Prognostic Biomarkers, PET‐CT, Hodgkin
lymphoma
No conflicts of interests pertinent to the abstract.
021 |PREDICTIVE VALUE OF QUANTITATIVE
18
F‐FDG‐PET‐CT
RADIOMICS ANALYSIS IN 174 PATIENTS WITH RELAPSED/
REFRACTORY CLASSICAL HODGKIN LYMPHOMA
J. Driessen
1
, G. J. C. Zwezerijnen
2
, H. Schöder
3
, A. J. Moskowitz
4
,
M. J. Kersten
1
, C. H. Moskowitz
5
, J. J. Eertink
6
, T. van de Brug
7
,
H. C. W. de Vet
7
, O. S. Hoekstra
2
, J. M. Zijlstra
6
, R. Boellaard
2
1
Amsterdam UMC, University of Amsterdam, LYMMCARE, Cancer
Center Amsterdam, Department of Hematology, Amsterdam,
Netherlands,
2
Amsterdam UMC, Vrije Universiteit Amsterdam, Cancer
Center Amsterdam, Department of Radiology and Nuclear Medicine,
Amsterdam, Netherlands,
3
Memorial Sloan Kettering Cancer Center,
Department of Radiology, New York, New York, USA,
4
Memorial Sloan
Kettering Cancer Center, Department of Medicine, New York, New
York, USA,
5
Sylvester Comprehensive Cancer Center, Department of
Medicine, Miami, Florida, USA,
6
Amsterdam UMC, Vrije Universiteit
Amsterdam, Cancer Center Amsterdam, Department of Hematology,
Amsterdam, Netherlands,
7
Amsterdam Public Health research institute,
Department of Epidemiology and Data Science, Amsterdam,
Netherlands
Introduction: About 20% of patients with classical Hodgkin lym-
phoma (cHL) relapse or are primary refractory to first‐line treatment
and require second‐line therapy followed by autologous stem cell
transplant. There is no one standard second‐line therapy and it is
possible that not all patients require such an aggressive approach to
achieve cure. Quantitative analysis of baseline
18
F‐FDG‐PET‐CT
scans could provide a comprehensible risk‐assessment complemen-
tary to clinical risk‐factors.
Methods: We analysed baseline
18
F‐FDG‐PET‐CT scans from r/r cHL
patients treated within three clinical trials with ICE, ICE and bren-
tuximab vedotin (BV) or DHAP and BV. For the clinical risk model we
used the following parameters: primary refractory vs relapse, age,
Ann Arbor stage and B‐symptoms. Metabolic tumor volume (MTV)
was calculated using a fixed threshold of standard uptake value (SUV)
≥4.0. Radiomics features were extracted in compliance with the
Image Biomarker Standardization Initiative. We developed a predic-
tive model for 3‐year time to progression (TTP) using logistic
SUPPLEMENT ABSTRACTS
-
49
regression with backward selection on robust radiomics features, e.g.
SUVpeak (highest 1mL region FDG uptake) and several novel dis-
persity features, representing dissemination and differences in vol-
ume and SUV of lesions within a patient. Results were cross‐validated
(CV) and validated in an independent external cohort. High‐risk
groups were defined based on the prevalence of events in the
training cohort (22/110; 20%).
Results: We included 174 r/r cHL patients; n =110 in the training set
(BV‐DHAP and BV‐ICE cohort) and n =64 in the validation set (ICE
cohort). The clinical model resulted in an area under the curve (AUC)
of 0.81 on the training set (tAUC), CV‐AUC of 0.76 and AUC of 0.74
on the validation set (vAUC).
Radiomics analysis resulted in a selection of 6 PET features: MTV and
5 dispersity features. The radiomics model showed a tAUC of 0.73,
CV‐AUC of 0.63 and vAUC of 0.70. Combining clinical and radiomics
parameters yielded a tAUC of 0.90, CV‐AUC of 0.79 and vAUC of
0.77.
Using the combined model on the training set, patients in the high‐
risk group (n =22) had a 3‐year TTP of 38% vs 90% for patients in
the low‐risk group (n =88; p <0.0001; Fig1A). In the validation set,
the 3‐year TTP was 39% vs 80% for high‐(n =13) and low‐risk pa-
tients (n =51; p =0.0011; Fig1B). In Fig1C we included an example
of PET‐CT scans of two patients with stage IV disease and a high and
low prediction score.
Conclusion: This is the first radiomics analysis in a large cohort of
r/r cHL patients. Combining radiomics and clinical features results
in a strong prediction model for 3‐year TTP with a tAUC of 0.90,
CV‐AUC of 0.79 and a vAUC of 0.77. The model uses robust PET
50
-
SUPPLEMENT ABSTRACTS
features that adress inter‐lesional heterogeneity in distance,
metabolic volume and SUV. Therefore, this model is suitable for
application in clinical trials and could guide risk‐stratified treat-
ment in r/r cHL.
EA ‐previously submitted to EHA 2021.
The research was funded by: SHOW foundation (Amsterdam
UMC donation fund to support hematology/oncology scientific
research)
Keywords: Diagnostic and Prognostic Biomarkers, PET‐CT, Hodgkin
lymphoma
No conflicts of interests pertinent to the abstract.
022 |DEVELOPMENT AND VALIDATION OF A PET
RADIOMICS PROGNOSTIC MODEL FOR DIFFUSE LARGE B
CELL LYMPHOMA
L. Ceriani
1
, L. Milan
1
, L. Cascione
2
, G. Gritti
3
, F. Dalmasso
4
,
F. Esposito
5
, Säm. Schär
6
, A. Bruno
7
, S. Dirnhofer
8
, L. Giovanella
1
,
S. Hayoz
6
, C. Mamot
9
, A. Rambaldi
3
, S. Chauvie
4
, E. Zucca
5
1
Ente Ospedaliero Cantonale, Clinic of Nuclear Medicine and PET/CT
Center, Lugano, Switzerland,
2
Università della Svizzera Italiana, Institute
of Oncology Research, Faculty of Biomedical Sciences, Bellinzona,
Switzerland,
3
Azienda Ospedaliera Papa Giovanni XXIII, Hematology Unit,
Bergamo, Italy,
4
Santa Croce e Carle Hospital, Medical Physics Unit,
Cuneo, Italy,
5
Ente Ospedaliero Cantonale, Institute of Southern
Switzerland, Clinic of Medical Oncology, Bellinzona, Switzerland,
6
Swiss
Group for Clinical Cancer Research (SAKK), Swiss Group for Clinical
Cancer Research (SAKK) Coordinating Center, Bern, Switzerland,
7
Azienda
Ospedaliera Papa Giovanni XXIII, Department of Nuclear Medicine,
Bergamo, Italy,
8
University Hospital Basel, Institute of Medical Genetics
and Pathology, Basel, Switzerland,
9
Cantonal Hospital Aarau, Division of
Oncology, Aarau, Switzerland
Introduction: Functional parameters derived from positron emission
tomography/computed tomography (PET/CT) seem promising bio-
markers in various lymphoma subtypes. The present study investigated
the prognostic value of PET/CT radiomics features in diffuse large B‐
cell lymphoma (DLBCL) patients uniformly treated with standard
immunochemotherapy (R‐CHOP regimen, either every 14 or 21 days).
Methods: Using the PyRadiomics Python package, 108 radiomics
features were extracted from the baseline PET/CT scans of a
testing set of 133 patients enrolled in the SAKK 38/07 prospective
clinical trial of the Swiss Group for Clinical Cancer Research
(SAKK). We used Spearman correlation test to select uncorrelated
features. The international prognostic indexes, the main clinical
parameters and the standard PET metrics were included, together
with 52 radiomics features, in a least absolute shrinkage and se-
lection operator (LASSO) Cox regression to assess their impact on
cause‐specific (CSS) and progression‐free (PFS) survival. A linear
combination of the resulting parameters generated a prognostic
radiomics score (RS) whose area under the curve (AUC) was
calculated by receiver operating characteristic (ROC) analysis. The
RS prognostic efficacy was validated in an independent set of 107
DLBCL patients.
Results: LASSO Cox regression identified four radiomics features
(GLCM_SumOfSquares*, Shape_Maximum3Diameter/BSA*, GLSZM_
GrayLevelNonUniformityNormalized*, GLDM_GrayLevelVariance*)
predicting PFS in the SAKK 38/07 cohort. The derived RS showed
a significant capability to foresee PFS in both testing (AUC, 0.709;
95%CI, 0.623‐0.784; P <0.001) and validation (AUC, 0.706; 95%
CI, 0.610‐0.790; P <0.001) sets. RS maintained its prognostic
value (HR, 2.1; 95%CI, 1.4‐3.2) after controlling for MTV in
multivariable Cox regression and was significantly associated also
with CSS in testing (AUC, 0.721; 95%CI, 0.636‐0.795; P <0.001)
and validation (AUC, 0.763; 95%CI, 0.671‐0.840; P <0.0001) sets.
Patient stratification according to RS quartiles identified subgroups of
patients with a progressively shorter PFS. Patients in the first and
second quartiles had a significantly better survival than those with RS
values above the median. A prognostic index could be built in both
cohorts separating 3 groups of patients with significantly different PFS
and CSS: low risk (1st and 2nd quartile) intermediate risk (3rd quartile)
and high‐risk group (4th quartile). This index showed better predictive
accuracy in comparison with clinical international prognostic indices.
Conclusions: PET‐derived radiomics may improve the prediction
of outcome in DLBCL patients treated with conventional
immunochemotherapy.
*For the feature description: https://pyradiomics.readthedocs.io/en/
latest/features.html
Keywords: Diagnostic and Prognostic Biomarkers, PET‐CT,
Aggressive B‐cell non‐Hodgkin lymphoma
No conflicts of interests pertinent to the abstract.
SUPPLEMENT ABSTRACTS
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51
SESSION 3: AGGRESSIVE LYMPHOMAS
023 |CLONAL HEMATOPOIESIS IS ASSOCIATED WITH
INFERIOR PROGNOSIS IN NEWLY DIAGNOSED DIFFUSE LARGE
B‐CELL LYMPHOMA PATIENTS
J. Boegeholz
1
, S. Alig
1
, B. Sworder
1
, C. Macaulay
1
, A. Craig
1
,
U. Dührsen
2
, A. Hüttmann
2
, D. Miklos
3
, M. Frank
3
, M. Diehn
4
,
D. Kurtz
1
, A. Alizadeh
1
1
Stanford University, Oncology, Stanford, USA,
2
University Hospital
Essen, Hematology, Essen, Germany,
3
Stanford University, BMT and Cell
Therapy, Stanford, USA,
4
Stanford University, Radiation Oncology,
Stanford, USA
Introduction: Clonal hematopoiesis of indeterminate potential
(CHIP) involves the accumulation of hematopoietic cells harboring
somatic mutations in the context of largely normal blood cell
counts. In patients (pts) without neoplasms, CHIP is associated
with future risk of myeloid malignancies and increased cardiovas-
cular risk. Pts with relapsed/refractory (r/r) Non‐Hodgkin
Lymphoma (NHL) carrying CHIP mutations prior to autologous
transplantation were found to have inferior outcome (Gibson, JCO
2017). Given the high frequency of PPM1D mutations identified in
this group, a significant share of these mutations is likely therapy‐
associated. The role of CHIP in newly diagnosed NHL remains
poorly described.
Methods: We studied 134 pts with previously untreated diffuse
large B Cell lymphoma (DLBCL) treated within the Phase III PETAL
trial as well as 60 pts with r/r disease who underwent Axicabta-
gene Ciloleucel therapy at Stanford University. Non‐silent CHIP
mutations in 15 canonical genes at variant allele frequencies ≥2%
were called using Cancer Personalized Profiling by Deep
Sequencing (CAPP‐Seq) of leukocytes isolated from the peripheral
blood.
Results: CHIP mutations were found in a similar fraction of 14/134
pts (10.4%) with untreated DLBCL and 10 of 60 pts (16.6%) with r/r
disease (p =0.24). The gene most commonly affected by CHIP in
untreated pts was DNMT3A (8/14 pts followed by TET2, TP53 (2/14
each) and CBL (Figure 1B). In contrast, in pts with r/r disease, we
identified PPM1D mutations in 3/10 cases, as well as mutations in
FIGURE 1 CHIP in previously untreated and r/r DLBCL: inferior event‐free survival of pts with CHIP prior to frontline, but not salavage,
therapy (A). Oncoplot of 14 untreated and 10 r/r pts with CHIP mutations (B). No significant difference in demand of Erythrocyte transfusions
(C), Thrombocyte transfusions (D) and infections (E) between pts +/‐CHIP mutation after frontline cytotoxic therapy
52
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SUPPLEMENT ABSTRACTS
DNTM3A (4/10), TP53 (2/10), ASXL1 (1/10) and CBL (1/10). CHIP was
associated with age in newly diagnosed DLBCL (p <0.01), but not IPI
Score, tumor volume and tumor DNA (ctDNA) level in plasma.
Strikingly, previously untreated pts with CHIP had a significant
inferior overall (OS) and event‐free survival (EFS) (p =0.048 and p =
0.024 respectively) (Figure 1A) following immunochemotherapy with
curative intent. In contrast, no such impact of CHIP was observed in
rrDLBCL treated with Axicabtagene Ciloleucel (p =0.99 and p =
0.35, respectively). CHIP was associated with lower DLBCL response
rates: among evaluable pts without CHIP, 98% achieved a complete
or partial remission (CR/PR) compared to only 82% in pts with CHIP
(p =0.05). Of note, therapy‐related myelosuppression appeared
similar in newly diagnosed DLBCL pts with and without CHIP, as we
observed no significant difference in transfusion needs or infection
rates (Figure 1C,D,E).
Conclusions: In this study CHIP mutations were detected in 12.4% of
DLBCL pts. While CHIP is associated with lower response rates and
inferior survival outcomes after frontline cytotoxic therapy of
DLBCL, this affect appears context‐specific, since it was not observed
in the rrDLBCL pts treated with CART19. Of interest, the mutational
CHIP landscape differed between our 2 cohorts, suggesting that
cytotoxic therapy shapes CHIP evolution.
The research was funded by: Swiss Cancer League
Keywords: Genomics, Epigenomics, and Other ‐Omics, Tumor Biology
and Heterogeneity
No conflicts of interests pertinent to the abstract.
024 |WHOLE GENOME SEQUENCING OF MATCHED PRIMARY
AND RELAPSED DLBCL REVEALS DISTINCT EVOLUTIONARY
DYNAMICS ASSOCIATED WITH RELAPSE TIMING
L. K. Hilton
1
, B. Collinge
1
, C. K. Rushton
2
, S. Ben‐Neriah
1
, K. Dreval
2
,
B. M/c. Grande
3
, M. Boyle
1
, B. Meissner
1
, G. W. Slack
1
, P. Farinha
1
,
J. W. Craig
1
, A. S. Gerrie
1
, C. Freeman
1
, D. Villa
1
, K. J. Savage
1
,
L. H. Sehn
1
, M. A. Marra
4
, C. Steidl
1
, R. D. Morin
2
, D. W. Scott
1
1
BC Cancer, Centre for Lymphoid Cancer, Vancouver, Canada,
2
Simon
Fraser University, Molecular Biology and Biochemistry, Burnaby, Canada,
3
Sage Bionetworks, Seattle, Washington, USA,
4
Canada's Michael Smith
Genome Sciences Centre, BC Cancer Research Institute, Vancouver,
Canada
Introduction: Diffuse large B‐cell lymphoma (DLBCL) is a genetically
heterogeneous disease with poor outcomes for the 40% of patients
who relapse or are refractory to frontline therapy. To explore genetic
changes associated with relapse, we applied fluorescence in situ hy-
bridization (FISH), gene expression profiling, and whole genome
sequencing (WGS) to two or more DLBCL biopsies from patients with
relapsed or refractory disease.
Methods: Archival paraffin biopsies with DLBCL morphology were
selected from 109 R‐CHOP‐treated patients, of which 55% had a
detectable low‐grade lymphoma at some point in their disease
course. Recurrences were defined as primary refractory (REFR, n =
24), early relapse (ER, n =29), or late relapse (LR, n =56) within <9,
9‐24, or >24 months from the first DLBCL biopsy, respectively.
Break‐apart FISH (n =101 pairs) was used to identify oncogene
translocations and the NanoString DLBCL90 assay (n =106 pairs)
identified cell‐of‐origin (COO) subgroups. Simple somatic mutations
(SSMs) were identified from WGS (n =52 tumour pairs plus matched
constitutional DNA) using an ensemble of four variant callers
(Strelka2, LoFreq, Mutect2 and SAGE), and somatic copy number
variations (CNVs) were detected using Battenberg. The LymphGen
classifier was applied to assign genetic subgroups.
Results: MYC and BCL6 translocation status was discordant be-
tween time points in 16% and 15% of tumour pairs, respectively.
BCL2 translocations were concordant in all cases, consistent with
their acquisition during VDJ recombination early in B‐cell differ-
entiation. Among pairs with DLBCL90 data, 9% (one ER and 6 LR)
were discordant for COO, excluding cases that were unclassified at
either time point. Of the 52 pairs with WGS, LymphGen classified
27 primary tumors and 31 secondary tumors, and the classification
was discordant in only one of 23 pairs that were classified at both
time points. The mutational repertoire between time points in
REFR pairs was strikingly consistent, reflecting little evolution.
Interestingly, despite shared mutations and largely concordant
genetic subgroup assignments, ER and LR pairs exhibited striking
genetic divergence with mutation patterns indicative of branching
evolution from a shared precursor cell. In spite of this divergence,
unique driver mutations and aberrant somatic hypermutation ten-
ded to affect the same genes in both tumours. Figure 1shows a
representative LR pair from a patient with no record of low‐grade
disease.
Conclusions: In contrast to REFR DLBCL, LR tumours frequently
represent new disease with significant genetic divergence yet shared
biology with the primary disease. This is consistent with the hy-
pothesis that DLBCLs arising from a common progenitor undergo
convergent evolution and rely on common oncogenic pathways while
also providing an explanation for the more frequent retained che-
mosensitivity in later DLBCL recurrence.
Keywords: Genomics, Epigenomics, and Other ‐Omics, Tumor Biology
and Heterogeneity, Aggressive B‐cell non‐Hodgkin lymphoma
Conflicts of interests pertinent to the abstract
R. D. Morin
Other remuneration: Named inventor on the DLBCL90 patent.
D. W. Scott
Other remuneration: Named inventor on the DLBCL90 patent.
SUPPLEMENT ABSTRACTS
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53
54
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SUPPLEMENT ABSTRACTS
025 |PHASED VARIANTS IMPROVE DLBCL
MINIMAL RESIDUAL DISEASE DETECTION AT THE END
OF THERAPY
D. M. Kurtz
1
, J. J. Chabon
2
, J. Soo
1
, L. Co Ting Keh
1
, S. Alig
1
,
A. Schultz
1
, M. C. Jin
1
, F. Scherer
3
, A. F. M. Craig
1
, C. L. Liu
1
,
U. Dührsen
4
, A. Hüttmann
4
, R.‐O. Casasnovas
5
, J. R. Westin
6
,
M. Roschewski
7
, W. H. Wilson
7
, G. Gaidano
8
, D. Rossi
9
, M. Diehn
10
,
A. A. Alizadeh
1
1
Stanford University, Medicine, Division of Oncology, Stanford,
California, USA,
2
Foresight Diagnostics, Research and Development,
Aurora, Colorado, USA,
3
Freiburg University Medical Center,
Hematology, Freiburg, Germany,
4
University Hospital Essen,
Hematology, Essen, Germany,
5
Hopital F. Mitterrand, CHU Dijon and
INSERM 1231, Hematology, Dijon, France,
6
MD Anderson Cancer
Center, Department of Lymphoma/Myeloma, Houston, Texas, USA,
7
National Cancer Institute, Lymphoid Malignancies Branch, Bethesda,
Maryland, USA,
8
University of Eastern Piedmont, Division of
Hematology, Department of Translational Medicine, Novara, Italy,
9
Oncology Institute of Southern Switzerland and Institute of Oncology
Research, Hematology, Bellinzona, Switzerland,
10
Stanford University,
Radiation Oncology, Stanford, California, USA
Background: Detection of circulating tumor DNA (ctDNA) has
prognostic value in diverse tumors, including DLBCL. Despite uses for
assessing molecular response to therapy, current methods using
immunoglobulin or hybrid‐capture sequencing have suboptimal
sensitivity, particularly when disease‐burden is low. This contributes
to a high false negative rate at key milestones such as at the end of
therapy (EOT; Kumar A, ASH 2020). We explored the utility of
detecting multiple mutations (phased variants, PVs, Fig 1A) on indi-
vidual cell‐free DNA (cfDNA) strands to improve MRD in DLBCL.
Methods: We applied Phased Variant Enrichment and Detection
Sequencing (PhasED‐Seq) to track PVs from 485 specimens from 117
DLBCL patients undergoing first‐line therapy. We sequenced cfDNA
prior to, during, and after therapy to assess the prognostic value of
MRD. We compared the performance of PhasED‐Seq to current
techniques, including SNV‐based CAPP‐Seq and duplex sequencing.
Results: To establish a detection limit, we compared the background
error‐profile of PVs and SNVs in healthy cfDNA. PVs demonstrated a
lower background profile than SNVs, even when considering duplex
molecules (n =12; 8.0e‐7 vs 3.3e‐5 and 1.2e‐5; P <0.0001; Fig 1B).
We also assessed sensitivity within a ctDNA limiting dilution series
from 3 patients, simulating tumor fractions from 0.1% to 0.00005%
(1:2,000,000). PhasED‐Seq outperformed SNV and duplex based
FIGURE 1 (A) structure of phased variants(PVs). (B) background signal from cell‐free DNA sequencing for SNVs with error suppression,
duplex SNVs, and PVs across 12 control samples. (C) dilution series comparing SNV‐based CAPP‐Seq, duplex sequencing, PhasED‐Seq. (D)
stratification of patients with DLBCL based on ctDNA at the end of therapy using SNV‐based methods or PhasED‐Seq. (E) Performance
metrics (specificity, sensitivitiy, and AUC) for identification of ctDNA residual disease by SNV‐based methods and PhasED‐Seq at key
landmarks in DLBCL, including pretreatment, cycle 2 day 1, cycle 3 day 1, and at the end of therapy
SUPPLEMENT ABSTRACTS
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55
methods for recovery of expected tumor content below 0.01% (P <
0.0001 and P =0.005 respectively by paired t‐test; Fig 1C).
We then explored disease detection in clinical samples. We identified
SNVs and PVs from pretreatment tumor or plasma and followed
these variants in serial cfDNA. Using SNV‐based methods, 40% and
59% of patients had undetectable ctDNA after 1 or 2 cycles (n =82
and 88). However, 24% and 25% of these cases had detectable
ctDNA by PhasED‐Seq. Importantly, MRD detection by PhasED‐Seq
was prognostic for event‐free survival even in patients with unde-
tectable ctDNA by SNVs. We next explored the utility of PhasED‐Seq
at the EOT in 19 subjects, 5 of whom experienced eventual disease
progression. While only 2/5 cases with progression had detectable
disease at EOT using SNVs, PhasED‐Seq detected all 5/5 cases
(Fig 1D). PhasED‐Seq also correctly identified all patients (14/14)
without clinical relapse as having no residual disease, including one
patient who discontinued therapy after1 cycle due to toxicity, but
remains in remission >5 years after this single treatment. This
resulted in superior classification of patients for EFS using PVs
compared with SNVs (C‐statistic: 0.98 vs 0.60, P =0.02, Fig 1E).
Conclusions: Tracking PVs results in significantly lower background
rates than SNV‐based approaches, enabling detection to parts per
million range. PhasED‐Seq improves disease detection in DLBCL at
the EOT, suggesting it is ideal for use in MRD‐driven consolidative
approaches.
EA ‐previously submitted to ASCO 2021
The research was funded by: National Cancer Institute
(R01CA233975 and R01CA188298 to A.A.A. and M.D.,
K08CA241076 to D.M.K.), the Virginia and D.K. Ludwig Fund for
Cancer Research (A.A.A. and M.D.), and the Damon Runyon Cancer
Research Foundation (PST#09‐16 to D.M.K. and DR‐CI#71‐14 to A.
A.A).
Keywords: Liquid biopsy, Minimal residual disease, Aggressive B‐cell
non‐Hodgkin lymphoma
Conflicts of interests pertinent to the abstract
D. M. Kurtz
Consultant or advisory role: Roche, Genentech, Foresight Diagnostics
Stock ownership: Foresight Diagnostics
J. J. Chabon
Employment or leadership position: Foresight Diagnostics
Stock ownership: Foresight Diagnostics
R.‐O. Casasnovas
Consultant or advisory role: Roche
D. Rossi
Research funding: Gilead, Janssen, Roche, AbbVie
M. Diehn
Consultant or advisory role: Roche, AstraZeneca, Illumina, RefleXion,
BioNTech, Foresight Diagnostics
Stock ownership: Foresight Diagnostics, CiberMed
Research funding: Varian Medical Systems, Illumina
A. A. Alizadeh
Consultant or advisory role: Foresight Diagnostics, Roche, Gen-
entech, Janssen, Pharmacyclics, Gilead, Celgene, Chugai
Stock ownership: FortySeven, CiberMed, Foresight Diagnostics
Research funding: Celgene, Pfizer
026 |GENETIC SUBTYPE GUIDED RITUXIMAB‐BASED
IMMUNOCHEMOTHERAPY IMPROVES OUTCOME IN NEWLY
DIAGNOSED DIFFUSE LARGE B‐CELL LYMPHOMA: FIRST
REPORT OF A RANDOMIZED PHASE 2 STUDY
M. Zhang
1
, P. Xu
1
, L. Wang
1
, S. Cheng
1
, W. Zhao
1
1
Shanghai Ruijin Hospital, Department of Hematology, Shanghai,
China
Introduction: Genetic subtypes of diffuse large B‐cell lymphoma
(DLBCL) have distinct oncogenic pathway feature, gene expression
phenotype, and variable clinical outcome. We aimed to investigate
whether adding novel targeted agents to R‐CHOP (R‐CHOP‐X) based
on genetic subtypes could improve clinical efficacy in newly diag-
nosed DLBCL.
Methods: This was a randomized phase II study comparing R‐
CHOP‐X with R‐CHOP in newly diagnosed DLBCL
(NCT04025593). Eligible patients were aged 18‐80 years, and IPI
risk of intermediate or high (IPI≥2). All patients were treated with
standard R‐CHOP for the first cycle, and were randomized 1:1 to
R‐CHOP‐X or R‐CHOP for the remaining 5 cycles. Targeted
sequencing was performed on formalin‐fixed paraffin‐embedded
tumor samples at diagnosis. We used a simplified method to
classify patients into six genetic subtypes MCD, BN2, N1, EZB,
TP53 and NOS, using mutations in 18 genes, BCL2 translocation,
and BCL6 fusion. MCD and BN2 patients were treated with BTK
inhibitor ibrutinib 420 mg/d, N1 and NOS patients with immuno-
modulatory agent lenalidomide 25mg d1‐10, EZB patients with
histone deacetylase inhibitor tucidinostat 20mg d1, 4, 8, 11, and
TP53 patients with intravenous demethylating agent decitabine 10
mg/m
2
d1‐5 followed by standard R‐CHOP. The primary endpoint
was complete response rate. Secondary endpoints included
progression‐free survival (PFS), overall survival (OS), overall
response rate, and safety.
Results: A total of 128 patients were enrolled (n =64 per arm)
between July 17th, 2019 to December 29th, 2020. Baseline clinical
characteristics were similar between arms, with a median age of
64 (range 25‐74), 52% male, 83% ECOG 0‐1, 77% stage III/IV, and
65% IPI≥3 for all patients. According to Hans algorithm, 62%
patients were categorized as non‐germinal B‐cell subtype and 36%
as MYC/BCL2 double expression. Regarding genetic subtypes, 20%,
18%, 4%, 2%, 16% and 39% patients were classified into MCD,
56
-
SUPPLEMENT ABSTRACTS
BN2, N1, EZB, TP53, and NOS subtype, respectively. Until
March 1st, 2021, all patients received at least 3 cycles of immu-
nochemotherapy and 107 patients were available for response
evaluation. The complete and overall response rates were 85% and
91% in R‐CHOP‐X arm, and 65% and 72% in R‐CHOP arm,
respectively. With a median follow‐up of 14.1 months, 1‐year PFS
and OS rates were 96% and 98% in R‐CHOP‐X arm, and 79% and
94% in R‐CHOP arm, respectively (PFS: HR 0.22, 95%CI 0.09‐0.61;
OS: HR 0.28, 95%CI 0.05‐1.60). The most common grade 3/4
adverse events (AEs) for R‐CHOP‐X vs R‐CHOP were neutropenia
(81% vs 75%), thrombocytopenia (31% vs 11%), anemia (25%
vs 20%), and febrile neutropenia (20% vs 11%). For non‐
hematological AEs, grade 3 infection occurred in 3% vs 2%,
grade 3 gastrointestinal bleeding in 2% vs 3% in R‐CHOP‐X vs R‐
CHOP arm, respectively. No grade 4 non‐hematological AEs were
observed.
Conclusion: Genetic subtype guided R‐CHOP‐X showed encouraging
response and outcome in DLBCL.
Keywords: Aggressive B‐cell non‐Hodgkin lymphoma, Molecular
Targeted Therapies
No conflicts of interests pertinent to the abstract.
027 |BIOMARKER‐DRIVEN TREATMENT STRATEGY IN HIGH
RISK DIFFUSE LARGE B‐CELL LYMPHOMA: RESULTS OF A
NORDIC PHASE 2 STUDY
S. Leppä
1
, J. Jørgensen
2
, M‐L. Karjalainen‐Lindsberg
3
, K. Beiske
4
,
P. Nørgaard
5
, K. Drott
6
, A. Pasanen
1
, K. Karihtala
1
, S. Mannisto
1
,
B. Wold
7
, M. Brodtkorb
7
, Unn‐M. Fagerli
8
, T. S. Larsen
9
, L. Munks-
gaard
10
, Ø. Fluge
11
, S. Jyrkkiö
12
, P. d. N. Brown
13
, H. Holte
7
1
University of Helsinki and Helsinki University Hospital
Comprehensive Cancer Centre, Department of Oncology, Helsinki,
Finland,
2
Aarhus University Hospital, Department of Hematology,
Aarhus, Denmark,
3
Helsinki University Hospital, Department of
Pathology, Helsinki, Finland,
4
Oslo University Hospital, Department of
Pathology, Oslo, Norway,
5
Herlev and Gentofte Hospital, Department
of Pathology, Herlev, Denmark,
6
Skåne University Hospital,
Department of Oncology, Lund, Sweden,
7
Oslo University Hospital,
Department of Oncology, Oslo, Norway,
8
St. Olav's Hospital,
Department of Oncology, Trondheim, Norway,
9
Odense University
Hospital, Department of Hematology, Odense, Denmark,
10
Roskilde
Hospital, Department of Hematology, Roskilde, Denmark,
11
Haukeland University Hospital, Department of Oncology, Bergen,
Norway,
12
Turku University Hospital, Department of Oncology, Turku,
Finland,
13
Rigshospitalet, Department of Hematology, Copenhagen,
Denmark
Introduction: Survival of patients with high risk diffuse large B‐cell
lymphoma (DLBCL), particularly those with biological risk factors,
including translocation of BCL2 and MYC oncogenes (double hit; DH),
high BCL2 and MYC double protein expression (DPE) or deletion of
17p/p53 is suboptimal in response to standard immunochemother-
apy. We designed a Nordic Lymphoma Group (NLG‐LBC‐06) phase II
trial to evaluate feasibility and efficacy of a biological risk‐adapted
treatment strategy in young patients with high risk aggressive B‐
cell lymphoma.
Methods: Patients aged <65 years with high risk (age adjusted In-
ternational Prognostic Index (aaIPI)≥2 and/or site‐specific risk fac-
tors for central nervous system (CNS) progression) aggressive B‐cell
lymphoma were included. All patients received two cycles of ritux-
imab, cyclophosphamide, doxorubicin, vincristine, prednisone (R‐
CHOP) and high dose methotrexate, and depending on the biological
risk factors either four additional courses of biweekly R‐CHOP with
etoposide (no biological risk factors) or four dose‐adjusted etoposide,
doxorubicin, cyclophosphamide, vincristine, prednisone, and ritux-
imab (DA‐EPOCH‐R; biological risk factors). In addition, one course
of R and HD‐cytarabine was given to all patients. The biologically
high risk group consisted of patients with at least one of the following
factors: C‐MYC translocation, DH, 17p/p53 deletion, DPE, P53+and/
or CD5+. Central pathology review was performed by national
referral pathologists.
Results: Between Aug 2017 and Jan 2021, 120 patients were recruited
across 14 Nordic centers. At central pathology review, two cases were
excluded due to unsuccessful stratification. The median age of the
eligible patients was 55 years (range 19‐64). The majority of the pa-
tients had DLBCL not otherwise specified (78%), stage IV disease
(68%), elevated LDH (87%), and B‐symptoms (58%). Sixty patients
(50%) were stratified to the biologically high risk group. C‐MYC
translocation, DH, 17p/p53 deletion, DPE, P53+and CD5+was
observed in 20 (17%), 14 (12%), 18 (15%), 38 (32%), 17 (14%) and 7
(6%) of the cases, respectively. Complete metabolic response was
achieved in 63/81 (78%) patients. Treatment failure was recorded in 17
(14%) patients, five due to toxicity and 12 due to progression, including
one CNS event. After a median follow up of 20 months (2‐46), 2‐year
failure free survival (FFS), progression free survival (PFS) and overall
survival (OS) were 82%, 85% and 91%, respectively. PFS was 95% and
76% in biologically low‐and high‐risk patients. In a multivariate anal-
ysis with age and aaIPI, 17p/p53 deletion and CD5+remained signifi-
cant risk factors for poor outcome.
Conclusions: Stratification according to biological risk factors is
feasible. DA‐EPOCH‐R can overcome the adverse impact of biolog-
ical risk factors, apart from 17p/p53 deletion and CD5+.
The research was funded by: Academy of Finland, Finnish Cancer
Organizations, The Southern Finland National Cancer Center, Sigrid
Juselius Foundation, Helsinki University Hospital, Nordic Cancer
Union
SUPPLEMENT ABSTRACTS
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57
Keywords: Aggressive B‐cell non‐Hodgkin lymphoma, Combination
Therapies
No conflicts of interests pertinent to the abstract.
028 |LONG‐TERM ANALYSES FROM L‐MIND, A PHASE II
STUDY OF TAFASITAMAB PLUS LENALIDOMIDE (LEN) IN
PATIENTS (PTS) WITH RELAPSED OR REFRACTORY DIFFUSE
LARGE B‐CELL LYMPHOMA (R/R DLBCL)
J. Duell
1
, K. J. Maddocks
2
, E. González‐Barca
3
, W. Jurczak
4
,
A. M. Liberati
5
, A. Obr
6
, G. Gaidano
7
, P. Abrisqueta
8
, M. André
9
,
M. Dreyling
10
, T. Menne
11
, M. Dirnberger‐Hertweck
12
, J. Weir-
ather
13
, S. Ambarkhane
14
, G. Salles
15
1
Universitätsklinik Würzburg, Medizinische Klinik und Poliklinik II,
Würzburg, Germany,
2
Arthur G James Comprehensive Cancer Center,
Ohio State University Wexner Medical Center, Department of Internal
Medicine, Columbus, USA,
3
Institut Catalá d’Oncologia (ICO), Hospital
Duran i Reynals, IDIBELL, Universitat de Barcelona, Department of
Hematology, Barcelona, Spain,
4
Maria Sklodowska‐Curie National
Research Institute of Oncology, Department of Clinical Oncology, Kraków,
Poland,
5
Azienda Ospedaliera Santa Maria di Terni, Università degli Studi
di Perugia, Terni, Italy,
6
Palacký University and University Hospital Olo-
mouc, Department of Hemato‐Oncology, Olomouc, Czech Republic,
7
University of Piemonte Orientale Amedeo Avogadro, Division of Hema-
tology, Department of Translational Medicine, Novara, Italy,
8
Vall d’He-
bron Institute of Oncology (VHIO), Vall d’Hebron University Hospital,
Department of Hematology, Barcelona, Spain,
9
Université Catholique de
Louvain, CHU UCL Namur, Department of Haematology, Yvoir, Belgium,
10
University Hospital, Ludwig‐Maximilians, Munich, Germany,
11
Freeman
Hospital, Newcastle Upon Tyne Hospitals NHS Foundation Trust,
Department of Haematology, Newcastle Upon Tyne, UK,
12
MorphoSys
AG, Global Patient Safety, Planegg, Germany,
13
MorphoSys AG, Biosta-
tistics, Planegg, Germany,
14
MorphoSys AG, Clinical Development, Pla-
negg, Germany,
15
Hospices Civils de Lyon and Université de Lyon,
Hématologie, Lyon, France
FIGURE 1 Study flow chart (A), Kaplan Meier survival estimates for failure free survival (B) and progression free survival according to
double hit (C) and 17p deletion or CD5 positivity (D)
58
-
SUPPLEMENT ABSTRACTS
Introduction: L‐MIND (NCT02399085) is an ongoing, open‐label,
Phase II study evaluating safety and efficacy of the anti‐CD19
antibody tafasitamab +LEN in pts with R/R DLBCL and ECOG
status 0–2, who had received 1–3 prior systemic therapies
(including ≥1 CD20‐targeting regimen). Primary analyses and 2‐
year efficacy results were previously presented: we report an
updated efficacy analysis with ≥35 months’ follow‐up (data cut‐off:
Oct 30, 2020).
Methods: Pts received 28‐day [D] cycles [C] of tafasitamab (12 mg/kg
IV), once weekly during C1–3, with a loading dose on D4 of C1, then
every two weeks (Q2W) during C4–12. LEN (25 mg PO) was
administered on D1–21 of C1–12. After C12, progression‐free pts
SUPPLEMENT ABSTRACTS
-
59
received tafasitamab Q2W until disease progression. The primary
endpoint was objective response rate (ORR); secondary endpoints
were duration of response (DoR), progression‐free survival (PFS) and
overall survival (OS).
Results: Of 81 enrolled pts, 80 received tafasitamab +LEN and were
included in the full analysis set. As of October 30, 2020, and after
≥35 months’ follow‐up, 17 patients were still receiving tafasitamab
monotherapy. ORR was 57.5% (n =46), including a complete
response (CR) in 40% of pts (n =32) and a partial response (PR) in
17.5% of pts (n =14). Median estimated DoR was 43.9 months (95%
confidence interval [CI]: 26.1–not reached [NR]), and NR in pts who
achieved a CR (95% CI: 43.9–NR). Median estimated PFS was 11.6
months (95% CI: 6.3–45.7) (Fig.) and estimated 36‐month PFS was
41.1% (95% CI: 29.1–52.7). Median estimated OS was 33.5 months
(95% CI: 18.3–NR).
In pts who had received 1 vs ≥2 prior lines of therapy, ORR was
67.5% (n =27/40; CR: 47.5%; PR: 20.0%) vs 47.5% (n =19/40;
CR: 32.5%; PR: 15.0%). Median estimated DoR was 43.9 months
(95% CI: 9.1–NR) with 1 prior treatment and NR (95% CI: 15.0–
NR) with ≥2 prior treatments. Estimated median PFS and 36‐
month PFS were 23.5 months (95% CI: 7.4–NR) and 47.8% (95%
CI: 30.2–63.4) in pts with 1 prior treatment vs 7.6 months (95%
CI: 2.7–NR) and 34.3% (95% CI: 18.6–50.7) in those receiving ≥2
prior treatments. Median estimated OS was 45.7 months (95% CI:
24.6–NR) in pts with 1 prior treatment compared with 15.5
months (95% CI: 8.6–NR) in those receiving ≥2 prior treatments.
No unexpected toxicities or new safety signals emerged. The most
frequently reported Grade ≥3 hematological TEAEs were neu-
tropenia (0.91/pt year of exposure [PY]), thrombocytopenia (0.17/
PY), leukopenia (0.13/PY), anemia (0.09/PY), and febrile neutropenia
(0.06/PY).
Conclusions: With a median DoR of 43.9 months (NR for pts
achieving a CR), combination therapy with tafasitamab +LEN fol-
lowed by tafasitamab monotherapy provided durable responses in
pts with R/R DLBCL not eligible for ASCT, with a manageable safety
profile. These long‐term data indicate that this chemotherapy‐free
regimen can achieve prolonged disease control and survival benefit
in this pt population, especially at first relapse.
EA ‐previously submitted to ASCO and EHA 2021.
The research was funded by: MorphoSys AG, Planegg, Germany
Keywords: Aggressive B‐cell non‐Hodgkin lymphoma
Conflicts of interests pertinent to the abstract
J. Duell
Research funding: MorphoSys AG, Regeneron Pharmaceuticals
K. J. Maddocks
Honoraria: Pharmacyclics, Celgene, Seattle Genetics, MorphoSys AG,
Bristol‐Myers Squibb, Karyopharm Therapeutics, Kite/Gilead Sci-
ences, ADC Therapeutics, Genmab
Research funding: Pharmacyclics, Merck, Bristol‐Myers Squibb
E. González‐Barca
Consultant or advisory role: Janssen, Celgene, Gilead Sciences,
Kyowa Kirin, EUSA Pharma, AbbVie
Educational grants: Janssen, AbbVie, Roche
Other remuneration: Janssen, AbbVie, Takeda
W. Jurczak
Consultant or advisory role: Mei pharma, Debiopharm, Loxo, Takeda,
AstraZeneca, Beigene
Research funding: GSK, Acerta, Beigene, Nordic Nanovector, Debio-
pharm, Incyte, Genentech, Janssen, Loxo, Mei Pharma, MorphoSys,
Takeda, TG Therapeutics
A. M. Liberati
Consultant or advisory role: Incyte
Honoraria: Bristol and Mayers, Servier, Celgene, Abbvie, Amgen
Research funding: Novartis, Jannsen, Abbvie, Roche, Amgen, Sanofi
Genzyme, Celgene, BMS, Servier, Incyte, Pfizer, IQVIA, Doxopharma,
Verastem, Beigene, Oncopeptides, Karyopharma, Archigen, CTI Bio-
pharma Corp, Debiopharm, MorphoSys AG, Fibrogen, Mei Pharma,
Regeneron Pharmaceutical Inc, Dr Reddy's Laboratories
Educational grants: Amgen, Servier, Celgene, Roche, Takeda, Abbvie,
Novartis, Sanofi Genzyme, IQVIA, Verastem, BMS
A. Obr
Consultant or advisory role: Janssen
Honoraria: Roche, Janssen
Educational grants: Roche, Gilead Sciences, Janssen
Other remuneration: Roche
G. Gaidano
Consultant or advisory role: Janssen, Abbvie, AstraZeneca
Honoraria: Janssen, Abbvie, AstraZeneca
Educational grants: Janssen
Other remuneration: Janssen, Abbvie
P. Abrisqueta
Consultant or advisory role: Janssen, Celgene, Abbvie, AstraZeneca
Honoraria: Janssen, Celgene, Abbvie, AstraZeneca, Gilead Sciences
Other remuneration: Janssen, Celgene, Abbvie, AstraZeneca, Gilead
Sciences
M. Dreyling
Consultant or advisory role: AstraZeneca, Bayer, Beigene, Celgene,
Gilead Sciences, Janssen, Novartis, Roche
Honoraria: Bayer, Celgene, Janssen, Roche, Gilead Sciences
Research funding: Abbvie, Bayer, Celgene, Janssen, Roche
T. Menne
Consultant or advisory role: Kite/Gilead Sciences, Celgene, Novartis,
Amgen, Pfizer, Atara Biotherapeutics, Daiichi Sankyo/Lilly
Honoraria: Takeda, Janssen
Research funding: Janssen, AstraZeneca, Novartis
Educational grants: Amgen, Jazz Pharmaceuticals, Janssen, Celgene,
Kite/Gilead Sciences
Other remuneration: Kite/Gilead Sciences, Roche, Novartis, Pfizer
60
-
SUPPLEMENT ABSTRACTS
M. Dirnberger‐Hertweck
Employment or leadership position: MorphoSys AG
J. Weirather
Employment or leadership position: MorphoSys AG
S. Ambarkhane
Employment or leadership position: MorphoSys AG
Educational grants: MorphoSys AG
G. Salles
Consultant or advisory role: Roche/Genentech, Gilead Sciences,
Janssen, Celgene, Novartis, MorphoSys AG, Epizyme, Alimera Sci-
ences, Genmab, Debiopharm Group, Velosbio
SESSION 4: CHRONIC LYMPHOCYTIC LEUKEMIA
029 |ADAPTATION OF CHRONIC LYMPHOCYTIC LEUKEMIA
TO IBRUTINIB IS MEDIATED BY EPIGENETIC PLASTICITY OF
RESIDUAL DISEASE AND BY‐PASS SIGNALING VIA MAPK
PATHWAY
L. Terzi di Bergamo
1
, G. Forestieri
1
, J. W. Loh
2
, A. Singh
2
, V. Spina
1
,
A. Zucchetto
3
, A. Condoluci
4
, M. Faderl
1
, R. Koch
1
, A. Bruscaggin
1
,
K. Pini
1
, W. Wu
1
, D. Piffaretti
1
, T. Bittolo
3
, E. Tissino
3
, L. De Paoli
5
,
C. Deambrogi
5
, A. M. Frustaci
6
, F. Autore
7
, M. Merli
8
, L. Scarfò
9
,
S. Rasi
5
, J. Passweg
10
, R. Moia
5
, C. Martines
11
, P. Ghia
9
, F. Cavalli
12
,
E. Zucca
13
, B. Gerber
4
, S. Gillessen
13
, G. Stüssi
4
, M. Montillo
6
,
F. Passamonti
8
, M. Gregor
14
, L. Laurenti
7
, A. Tedeschi
6
, G. Gaidano
5
,
D. Efremov
11
, V. Gattei
3
, H. Khiabanian
2
, D. Rossi
15
1
Institute of Oncology Research, Laboratory of Experimental
Hematology, Bellinzona, Switzerland,
2
Rutgers Cancer Institute of New
Jersey, Center for Systems and Computational Biology, New Brunswick,
New Jersey, USA,
3
Centro di Riferimento Oncologico di Aviano (CRO),
IRCCS, Clinical and Experimental Onco‐Hematology Unit, Aviano, Italy,
4
Oncology Institute of Southern Switzerland, Clinic of Hematology,
Bellinzona, Switzerland,
5
University of Eastern Piedmont, Division of
Hematology, Department of Translational Medicine, Novara, Italy,
6
ASST Grande Ospedale Metropolitano Niguarda, Niguarda Cancer
Center, Department of Hematology, Milan, Italy,
7
Catholic University of
the Sacred Hearth, Fondazione Policlinico Universitario A. Gemelli,
Hematology Institute, Rome, Italy,
8
Ospedale di Circolo e Fondazione
Macchi, University of Insubria, Division of Hematology, Varese, Italy,
9
IRCCS San Raffaele Scientific Institute and Vita‐Salute San Raffaele
University, Strategic Research Program on CLL, Division of Experimental
Oncology, Milan, Italy,
10
University Hospital Basel, Department of
Haematology, Basel, Switzerland,
11
International Centre for Genetic
Engineering and Biotechnology, Molecular Hematology, Trieste, Italy,
12
Università della Svizzera Italiana, Institute of Oncology Research,
Bellinzona, Switzerland,
13
Oncology Institute of Southern Switzerland,
Clinic of Oncology, Bellinzona, Switzerland,
14
Cantonal Hospital
Lucerne, Division of Haematology and Central Haematology Laboratory,
Lucerne, Switzerland,
15
Institute of Oncology Research, Experimental
Hematology, Bellinzona, Switzerland
Background: Ibrutinib is highly active in CLL. The most typical
response to ibrutinib is partial remission (PR) with measurable min-
imal residual disease (MRD) in blood, which is believed to persist in
an inhibited/anergic state. Remission is usually maintained until the
development of genetically driven resistance.
Methods: Pre‐treatment CLL cells, and under treatment MRD were
systematically collected from 33 CLL patients who received ibrutinib
in the IOSI‐EMA001 and IOSI‐EMA003 studies. Samples were
characterized by multilayer systematic approaches, including high‐
dimensional single‐cell flow cytometry, bulk genomic, tran-
scriptomic, chromatin accessibility, and single cell RNA‐seq profiling.
Results: Deep DNA‐sequencing did not discover mutations of BTK or
PLCG2 neither in purified MRD cells nor in plasma ctDNA, confirming
that BTK and PLCG2 mutations are not implicated in MRD survival.
In general, the genetic composition of MRD remained constant across
timepoints, indicating that ibrutinib did not have any impact in
shaping its genomic diversity (Fig. A). Conversely, ibrutinib induced
chromatin dynamics in MRD resulting in a predominantly closed state
(Fig. B). Chromatin regions that became more accessible under
ibrutinib were enriched of binding sites for transcription factor that
lay downstream ERK signaling. Conversely, regions that turned into a
less accessible state were enriched for the binding sites of tran-
scription factor that laid downstream the CBM, calcium‐calmodulin,
p38 and JNK cascades emanating from the BCR. Consistently, at
transcriptomic level most of the differentially expressed genes be-
tween pre‐and post‐treatment samples were downregulated in
MRD, while only a fraction was upregulated. IL4, NF‐kB, metabolism
and proliferation signatures were downregulated in MRD, while
MAPK and RAS signatures were upregulated (Fig. C). CLL spleen
samples from TCL1 mouse model under ibrutinib treatment were
compared to untreated mice. The transcriptomic changes observed in
MRD residing in the murine tissue were comparable to patients’
MRD. Single‐cell transcriptomes revealed a distinct post‐treatment
cell population driven by MAPK activity which functionally pre‐
existed in a fraction of CLL cells of the baseline samples before
ibrutinib start (Fig. D). Surface antigen composition of MRD turned to
mount a higher density of BCR signalosome molecules. At the
signaling level, ibrutinib had no effect on the integrity of the RAS‐
BRAF‐MAPK‐ERK pathway protein expression. Upon crosslinking
of the BCR with anti‐IgM, but not after stimulation of TLR9 or CD40,
the density of expression of the pERK increased in MRD cells at
levels that were similar to those measured in the pre‐treatment
samples (Fig. E).
Conclusions: MRD under ibrutinib adapts its phenotype, mainly in an
epigenetic way to maintain functional competence of BCR signaling
through the MAPK pathway.
SUPPLEMENT ABSTRACTS
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61
Keywords: Genomics, Epigenomics, and Other ‐Omics, Molecular
Targeted Therapies, Chronic Lymphocytic Leukemia (CLL)
Conflicts of interests pertinent to the abstract
E. Zucca
Research funding: Janssen
D. Rossi
Honoraria: AbbVie, AstraZeneca, Janssen
Research funding: AbbVie, AstraZeneca, Janssen
030 |GENETIC MARKERS AND OUTCOME WITH FRONT
LINE OBINUTUZUMAB PLUS EITHER CHLORAMBUCIL
OR VENETOCLAX ‐UPDATED ANALYSIS OF THE CLL14
TRIAL
E. Tausch
1
, C. Schneider
1
, D. Yosifov
1
, S. Robrecht
2
, C. Zhang
2
,
O. Al‐Sawaf
2
, B. Eichhorst
2
, A.‐M. Fink
2
, J. Bloehdorn
1
,
K.‐A. Kreuzer
2
, M. Tandon
3
, Y. Jiang
4
, S. Y. Kim
5
, M. Porro Lura
6
,
H. Döhner
1
, K. Fischer
1
, M. Hallek
2
, S. Stilgenbauer
1
1
Ulm University, Department of internal medicine 3, Ulm, Germany,
2
University Hospital Cologne, Department I of Internal Medicine
and Center of Integrated Oncology Aachen Bonn Cologne
Duesseldorf, Cologne, Germany,
3
Roche Products Limited, Clinical
development, Welwyn Garden City, UK,
4
Genentech, Hematology,
South San Francisco, USA,
5
AbbVie, Medical, North Chicago,
United States of America,
6
F. Hoffmann‐La Roche, Ltd, Basel,
Switzerland
Background: In 2019 we provided initial analyses of the prognostic
and predictive value of genomic aberrations, IGHV mutation status
and gene mutations in the CLL14 trial comparing obinutuzumab
+chlorambucil (GClb) vs. obinutuzumab+venetoclax (VenG) in 432
patients (1:1) with coexisting conditions.
Methods: Genomic aberration, IGHV status and mutations in TP53,
NOTCH1,SF3B1 and other candidate genes were analyzed in 421 of
432 (94%) patients of the full trial cohort at baseline. This update
includes a) an extended follow‐up at a median of >4 years, b)
assessment of the prognostic value of minor mutations with a variant
allele fraction (VAF) of 2‐10% c) analysis of 113 samples at relapse
for acquired gene mutation.
Results: The prevalence of genomic aberrations considering hierar-
chical model was del(17p) 7%, del(11q) 18%, +(12q) 18% and del
(13q) single 35%. IGHV was unmutated in 60% of patients.
The prevalence of gene mutations with a VAF>10% was NOTCH1
23%, SF3B1 15%, ATM 13%, TP53 10%, XPO1 6%, RPS15 5%,
62
-
SUPPLEMENT ABSTRACTS
POT1 5%, BRAF,BIRC3,NFKBIE,EGR2,MYD88 and FBXW7 (all <5%).
Minor mutations (VAF 2‐10%) occurred in BIRC3 with an incidence of
5%, NOTCH1 5%, SF3B1 5%, ATM 4% and TP53 3%.
At a median follow‐up of 52 months, 199 events for PFS and 75 for
OS occurred in the ITT population. VenG was superior to GClb
regarding PFS in most genetic subgroups including del(17p) (HR =
0.3, p <0.01) and mutated (HR =0.4, p <0.01) and unmutated IGHV
(HR =0.3, p <0.001).
For GClb del(17p) (HR 3.2, p <0.001), del(11q) (HR 1.8, p <0.01),
unmutated IGHV (HR 3.1, p <0.0001) and mutations in ATM (HR 1.8,
p=0.01), BIRC3 (HR 3.0, p <0.01), NOTCH1 (HR 1.7, p <0.01),
NOTCH1 minor (HR 2.1, p =0.02) and SF3B1 (HR 1.6, p =0.03) were
associated with short PFS, while for VenG del(17p) (HR 3.2, p =
0.001), mutated TP53 (HR 2.4, p <0.01) and unmutated IGHV (HR
2.1, p =0.02) were prognostic.
OS was shorter with del(17p) and TP53 mutation in both treatment
arms (GClb: HR 5.7 and HR 3.1, VenG: HR 3.5 and HR 3.0, all p <
0.01) and with mutated SF3B1 (HR 2.0, p =0.05) and unmutated
IGHV (HR 2.8, p =0.01) in the GClb arm. In multivariate analysis,
GClb therapy, high risk for tumor lysis, IGHV mutation status, del
(17p), complex karyotype and BIRC3 mutations were independent
prognostic factors for PFS, while age, b2MG and del(17p) retained
independent significance for OS.
Comparative analysis of 88 paired samples at baseline and relapse
after GClb revealed acquisition of high risk variants such as TP53 (n
=4), BIRC3 (5), SF3B1 (3) and RPS15 (1). Among 25 paired samples
before and after VenG, a single acquired variant was found each in
TP53 and BIRC3. Of note, none of the relapse samples had acquired
mutations in BCL2.
Conclusions: IGHV mutation status and del(17p) proved to be
prognostic with VenG and GClb, while none of the other prognostic
factors besides TP53 affected outcome with VenG. After VenG no
BCL2 resistance mutations were identified at relapse supporting re‐
treatment concepts.
EA ‐previously submitted to EHA 2021.
The research was funded by: HoffmannLa Roche
Keywords: Diagnostic and Prognostic Biomarkers, Chronic Lympho-
cytic Leukemia (CLL)
Conflicts of interests pertinent to the abstract
E. Tausch
Consultant or advisory role: Roche, Janssen, Abbvie
Honoraria: Roche, Janssen, Abbvie
Research funding: Roche, Abbvie
Travel grants: Janssen
O. Al‐Sawaf
Employment or leadership position: Honoraria: Advisory boards:
Roche, Janssen, Gilead, Abbvie Personal fees: Roche, Janssen, Gilead,
Abbvie Research grants: Beigene
Consultant or advisory role: Roche, Janssen, Gilead, Abbvie
Honoraria: Roche, Janssen, Gilead, Abbvie
Research funding: Beigene
B. Eichhorst
Consultant or advisory role: AbbVie, AstraZeneca, Celgene, F.
Hoffmann‐LaRoche, Gilead, Janssen‐Cilag
Research funding: AbbVie, AstraZeneca, Celgene, F. Hoffmann‐
LaRoche, Gilead, Janssen‐Cilag
Travel grants: AbbVie, AstraZeneca, Celgene, F. Hoffmann‐LaRoche,
Gilead, Janssen‐Cilag
A.‐M. Fink
Honoraria: Janssen
Research funding: Celgene
Travel grants: Abbvie
K.‐A. Kreuzer
Consultant or advisory role: AbbVie, Amgen, F. Hoffmann‐LaRoche,
Gilead, Janssen‐Cilag and Mundipharm
Honoraria: AbbVie, Amgen, F. Hoffmann‐LaRoche, Gilead, Janssen‐
Cilag and Mundipharm
Research funding: AbbVie, Amgen, F. Hoffmann‐LaRoche, Gilead,
Janssen‐Cilag and Mundipharm
M. Tandon
Employment or leadership position: Roche
Y. Jiang
Employment or leadership position: Genentech
Stock ownership: Genentech
S. Y. Kim
Employment or leadership position: AbbVie
M. Porro Lura
Employment or leadership position: F. Hoffmann ‐La Roche Ltd
Stock ownership: F. Hoffmann ‐La Roche Ltd
K. Fischer
Honoraria: AbbVie and F. Hoffmann‐LaRocheTravel grants: Roche
M. Hallek
Consultant or advisory role: AbbVie, Amgen, Celgene, F. Hoffmann‐
LaRoche, Gilead, Janssen‐Cilag and Mundipharma.
Honoraria: AbbVie, Amgen, Celgene, F. Hoffmann‐LaRoche, Gilead,
Janssen‐Cilag and Mundipharma.
Research funding: AbbVie, Amgen, Celgene, F. Hoffmann‐LaRoche,
Gilead, Janssen‐Cilag and Mundipharma.
S. Stilgenbauer
Consultant or advisory role: AbbVie, Amgen, Boehringer‐Ingelheim,
Celgene, F. Hoffmann‐LaRoche, Genentech, Genzyme, Gilead, Glax-
oSmithKline, Janssen‐Cilag, Mundipharma, Novartis and
Pharmacyclics
Research funding: AbbVie, Amgen, Boehringer‐Ingelheim, Cel-
gene, F. Hoffmann‐LaRoche, Genentech, Genzyme, Gilead, Glaxo-
SmithKline, Janssen‐Cilag, Mundipharma, Novartis and
Pharmacyclics
Travel grants: AbbVie, Amgen, Boehringer‐Ingelheim, Celgene,
F. Hoffmann‐LaRoche, Genentech, Genzyme, Gilead, GlaxoSmithK-
line, Janssen‐Cilag, Mundipharma, Novartis and Pharmacyclics
SUPPLEMENT ABSTRACTS
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63
031 |VENETOCLAX‐OBINUTUZUMAB MODULATES CLONAL
GROWTH: RESULTS OF A POPULATION‐BASED MINIMAL
RESIDUAL DISEASE MODEL FROM THE RANDOMIZED CLL14
STUDY
O. Al‐Sawaf
1
, C. Zhang
1
, T. Lu
2
, M. Z. Liao
2
, A. Panchal
3
, S. Robrecht
1
,
T. Ching
4
, M. Tandon
3
, A.‐M. Fink
1
, E. Tausch
5
, M. Ritgen
6
,
S. Böttcher
7
, K.‐A. Kreuzer
1
, S. Kim
8
, D. Miles
9
, C. Wendtner
10
,
S. Stilgenbauer
5
, B. Eichhorst
1
, Y. Jiang
2
, M. Hallek
1
, K. Fischer
1
1
University Hospital of Cologne, Department I of Internal Medicine,
Cologne, Germany,
2
Genentec Inc., San Francisco, USA,
3
Roche
Products Limited, Welwyn Garden City, UK,
4
Adaptive Biotechnologies
Corp., Seattle, USA,
5
University Hospital Ulm, Department III of
Internal Medicine, Ulm, Germany,
6
University of Schleswig‐Holstein,
Department II of Internal Medicine, Kiel, Germany,
7
University Hospital
Rostock, Department III of Internal Medicine, Rostock, Germany,
8
AbbVie Inc., Chicago, USA,
9
Genentec Inc., Sunnyvale, USA,
10
Klinikum
Schwabing, Department of Hematology, Oncology, Immunology,
Palliative Care, Infectious Diseases and Tropical Medicine, Munich,
Germany
Introduction: The CLL14 study has established fixed‐duration
treatment with the BCL2 inhibitor venetoclax and the CD20 anti-
body obinutuzumab (Ven‐Obi) for patients (pts) with previously un-
treated chronic lymphocytic leukemia (CLL). The aim of this report is
to provide a population‐based exploratory analysis of MRD growth
dynamics and to compare growth trajectories after stopping Ven‐Obi
and chlorambucil‐Obi (Clb).
64
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SUPPLEMENT ABSTRACTS
Methods: Pts were randomized 1:1 to receive 12 cycles (cy) of
Ven with 6 cy of Obi or 12 cy of Clb with 6 cy of Obi. MRD
was analyzed by NGS (clonoSEQ Assay). Samples from peripheral
blood (PB) are collected every 3‐6 months. For the longitudinal
analyses of MRD growth dynamics, a population‐based logistic
growth model with nonlinear mixed effects (NLME) approach was
developed to estimate population and individual patient parame-
ters. Cases with at least two measurable timepoints were
included; data <LLOQ were incorporated by likelihood‐based
method. Prognostic markers were screened as covariates for
impact on key model parameters based on statistical and graphical
assessments.
Results: Of 432 enrolled pts, 216 were assigned to receive Clb‐Obi
and 216 to Ven‐Obi. At follow‐up month 30, 7 (3.2%) pts in the
Clb‐Obi arm and 58 (26.9%) pts in the Ven‐Obi arm had uMRD levels
<10
‐4
(Fig A,B). Based on the inclusion criteria for the population
analysis, 154 pts from Clb‐Obi and 153 pts from Ven‐Obi arm were
included. The model was well calibrated, and high concordance be-
tween observed and predicted values was confirmed (Fig C).
The median MRD level at EoT was significantly lower after Ven‐Obi
than after Clb‐Obi (10
‐6.00
vs 10
‐3.26
, p <2e‐16). Within the Ven‐Obi
arm, end of treatment MRD values did not differ between pts with
low‐risk and high‐risk features, such as IGHV status (10
‐5.79
for
mutated IGHV vs 10
‐6.12
for unmutated IGHV) or TP53 deletion/
mutation (10
‐5.38
for deletion/mutation vs 10
‐6.03
for non‐deleted/
mutated). The median MRD doubling time was longer after Ven‐Obi
than Clb‐Obi therapy (median days 84 versus 67 days, p =3.3e‐5)(Fig
D). The median time from EoT to MRD level increase to 10
‐2
was also
FIGURE 1
SUPPLEMENT ABSTRACTS
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65
